Evapotranspiration Retrieving Research Articles

Monitoring daily evapotranspiration over two California vineyards using Landsat 8 in a multi-sensor data fusion approach

Abstract California's Central Valley grows a significant fraction of grapes used for wine production in the United States. With increasing vineyard acreage, reduced water availability in much of California, and competing water use interests, it is critical to be able to monitor regional water use and evapotranspiration (ET) over large areas, but also in detail at individual field scales to improve water management within these viticulture production systems. This can be achieved by integrating remote sensing data from multiple satellite systems with different spatiotemporal characteristics. In this research, we evaluate the utility of a multi-scale system for monitoring ET as applied over two vineyard sites near Lodi, California during the 2013 growing season, leading into the drought in early 2014. The system employs a multi-sensor satellite data fusion methodology (STARFM: Spatial and Temporal Adaptive Reflective Fusion Model) combined with a multi-scale ET retrieval algorithm based on the Two-Source Energy Balance (TSEB) land-surface representation to compute daily ET at 30 m resolution. In this system, TSEB is run using thermal band imagery from the Geostationary Environmental Operational Satellites (GOES; 4-km spatial resolution, hourly temporal sampling), the Moderate Resolution Imaging Spectroradiometer (MODIS) data (1 km resolution, daily acquisition) and the new Landsat 8 satellite (sharpened to 30 m resolution, ~ 16 day acquisition). Estimates of daily ET generated in two neighboring fields of Pinot noir vines of different age agree with ground-based flux measurements acquired in-field during most of the 2013 season with relative mean absolute errors on the order of 19–23% (root mean square errors of approximately 1 mm d − 1 ), reducing to 14–20% at the weekly timestep relevant for irrigation management (~ 5 mm wk − 1 ). A model overestimation of ET in the early season was detected in the younger vineyard, perhaps relating to an inter-row grass cover crop. Spatial patterns of cumulative ET generally correspond to measured yield maps and indicate areas of variable crop moisture, soil condition, and yield within the vineyards that could require adaptive management. The results suggest that multi-sensor remote sensing observations provide a unique means for monitoring crop water use and soil moisture status at field-scales over extended growing regions, and may have value in supporting operational water management decisions in vineyards and other high value crops.

Estimation of Evapotranspiration and Crop Coefficients of Tendone Vineyards Using Multi-Sensor Remote Sensing Data in a Mediterranean Environment

The sustainable management of water resources plays a key role in Mediterranean viticulture, characterized by scarcity and competition of available water. This study focuses on estimating the evapotranspiration and crop coefficients of table grapes vineyards trained on overhead “tendone” systems in the Apulia region (Italy). Maximum vineyard transpiration was estimated by adopting the “direct” methodology for ETp proposed by the Food and Agriculture Organization in Irrigation and Drainage Paper No. 56, with crop parameters estimated from Landsat 8 and RapidEye satellite data in combination with ground-based meteorological data. The modeling results of two growing seasons (2013 and 2014) indicated that canopy growth, seasonal and 10-day sums evapotranspiration values were strictly related to thermal requirements and rainfall events. The estimated values of mean seasonal daily evapotranspiration ranged between 4.2 and 4.1 mm·d−1, while midseason estimated values of crop coefficients ranged from 0.88 to 0.93 in 2013, and 1.02 to 1.04 in 2014, respectively. The experimental evapotranspiration values calculated represent the maximum value in absence of stress, so the resulting crop coefficients should be used with some caution. It is concluded that the retrieval of crop parameters and evapotranspiration derived from remotely-sensed data could be helpful for downscaling to the field the local weather conditions and agronomic practices and thus may be the basis for supporting grape growers and irrigation managers.

Use of MODIS Images to Quantify the Radiation and Energy Balances in the Brazilian Pantanal

MODIS images during the year 2012 were used for modelling of the radiation and energy balance components with the application of the SAFER algorithm (Simple Algorithm for Evapotranspiration Retrieving) in the Brazilian Pantanal area. Pixels from the main sub-regions of Barão de Melgaço (BR), Paiaguás (PA) and Nhecolândia (NH) were extracted in order to process microclimatic comparisons. In general, the net radiation (Rn) relied much more on the global solar radiation (RG) levels than on water conditions and ecosystem types, in accordance with the low Rn standard deviation values. The fraction of the available energy used as latent heat flux (λE) were, on average, 65, 50 and 49% for the BR, PA and NH sub-regions, respectively. Horizontal heat advection, identified by the negative values of sensible heat flux (H), made several pixels with λE values higher than those for Rn in the middle of the year. Taking the evaporative fraction (Ef) as a surface moisture indicator, the Tree-Lined Savanna (TLS) was considered the moister ecosystem class, with 58% of the available energy being used as λE, while the driest one was the modified ecosystem Anthropogenic Changes (AC), presenting a λE/Rn fraction of 0.46. According to the spatial and temporal consistencies, and after comparisons with other previous point and large-scale studies, the SAFER algorithm proved to have sensibility to quantify and compare the large-scale radiation and energy balance components in the different ecosystems of the Brazilian Pantanal. The algorithm is useful for monitoring the energy exchange dynamics among the different terrestrial and aquatic ecosystem types throughout the seasons of the year.

Using Simplified Thermal Inertia to Determine the Theoretical Dry Line in Feature Space for Evapotranspiration Retrieval

With the development of quantitative remote sensing, regional evapotranspiration (ET) modeling based on the feature space has made substantial progress. Among those feature space based evapotranspiration models, accurate determination of the dry/wet lines remains a challenging task. This paper reports the development of a new model, named DDTI (Determination of Dry line by Thermal Inertia), which determines the theoretical dry line based on the relationship between the thermal inertia and the soil moisture. The Simplified Thermal Inertia value estimated in the North China Plain is consistent with the value measured in the laboratory. Three evaluation methods, which are based on the comparison of the locations of the theoretical dry line determined by two models (DDTI model and the heat energy balance model), the comparison of ET results, and the comparison of the evaporative fraction between the estimates from the two models and the in situ measurements, were used to assess the performance of the new model DDTI. The location of the theoretical dry line determined by DDTI is more reasonable than that determined by the heat energy balance model. ET estimated from DDTI has an RMSE (Root Mean Square Error) of 56.77 W/m2 and a bias of 27.17 W/m2; while the heat energy balance model estimated ET with an RMSE of 83.36 W/m2 and a bias of −38.42 W/m2. When comparing the coeffcient of determination for the two models with the observations from Yucheng, DDTI demonstrated ET with an R2 of 0.9065; while the heat energy balance model has an R2 of 0.7729. When compared with the in situ measurements of evaporative fraction (EF) at Yucheng Experimental Station, the ET model based on DDTI reproduces the pixel scale EF with an RMSE of 0.149, much lower than that based on the heat energy balance model which has an RMSE of 0.220. Also, the EF bias between the DDTI model and the in situ measurements is 0.064, lower than the EF bias of the heat energy balance model, which is 0.084.

Performance Assessment of the SEVIRI Evapotranspiration Operational Product: Results Over Diverse Mediterranean Ecosystems

Evapotranspiration (ET) is an important variable in weather systems and hydrometeorological modeling. In this paper, an extensive validation was carried out on the spinning enhanced visible and infrared imager (SEVIRI) ET operational product, evaluating its accuracy at selected European sites. Validation was performed through comparisons with in-situ eddy covariance measurements belonging to the CarboEurope IP network. Comparisons were performed for selected cloud-free days with a satisfactory energy balance ratio in 2011. A total of nine sites covering six land covers were used in validating the ET retrieval accuracy from the operational product. A series of statistical metrics was computed to evaluate the agreement, which also included explored the variability of site characteristics and influence of land cover on ET performances. Overall, a good agreement was reported between the satellite-derived ET estimates and the ground measurements (d-index = 0.755, root mean square deviation (RMSD) = 0.107 mm $\text{h}^{\mathrm {-1}})$ . A minor negative bias of −0.015 mm $\text{h}^{\mathrm {-1}}$ suggested only slight underestimation of the in-situ data. In terms of land cover, the highest agreement in ET was reported for the olive orchards and open shrubland sites ( ${\rm d-index} = 0.893/0.867$ , ${\rm RMSD} = 0.041/0.050~{\rm mm}~{\rm h}^{\mathrm {-1}})$ . A systematic ET underestimation by SEVIRI was found for all land cover types. Results of this study are largely in agreement to previous analogous validation studies of the product. Our findings support the potential value of the SEVIRI ET product for regional to mesoscale studies and practical applications. The latter is of particular importance for water limiting environments such as those found in the Mediterranean basin, as accurate information on ET rates can provide tremendous support in sustainable water resource management as well as policy and decision making.

Improving evaluation of climate change impacts on the water cycle by remote sensing ET-retrieval

Abstract. Population growth and intense consumptive water uses are generating pressures on water resources in the southeast of Spain. Improving the knowledge of the climate change impacts on water cycle processes at the basin scale is a step to building adaptive capacity. In this work, regional climate model (RCM) ensembles are considered as an input to the hydrological model, for improving the reliability of hydroclimatic projections. To build the RCMs ensembles, the work focuses on probability density function (PDF)-based evaluation of the ability of RCMs to simulate of rainfall and temperature at the basin scale. To improve the spatial calibration of the continuous hydrological model used, an algorithm for remote sensing actual evapotranspiration (AET) retrieval was applied. From the results, a clear decrease in runoff is expected for 2050 in the headwater basin studied. The plausible future scenario of water shortage will produce negative impacts on the regional economy, where the main activity is irrigated agriculture.

Evapotranspiration in Korea estimated by application of a neural network to satellite images

Previous biophysical and empirical models of evapotranspiration retrieval are difficult to parameterize because of the effects of the nonlinear biophysics of plants, terrestrial and solar radiation and soils, despite attempts made using various satellite products. In this study, the multilayer feed-forward neural network approach with Levenberg–Marquardt back propagation (LM-BP) was used to successfully estimate evapotranspiration using the input of various satellite-based products. When applying neural network training, value-added satellite-based products such as normalized difference vegetation index (NDVI), normalized difference water index (NDWI), land surface temperature (LST), air temperature and insolation are used instead of only spectral information from satellite sensors to reflect the spatial representativeness of the neural network. The evapotranspiration estimated from the neural network with input parameters showed better statistical accuracy than the MODIS products (MOD16) and Priestley–Taylor methods when compared with ground station eddy flux measurements, which were considered as reference data. Additionally, the temporal variation in neural network evapotranspiration well reflected seasonal patterns of eddy flux evapotranspiration, especially for the high cloudiness in the summer season.

Irrigation performance assessments for corn crop with Landsat images in the São Paulo state, Brazil

Actual evapotranspiration (ET) and crop coefficient (Kc) were modelled in a commercial farm with corn crop. The plots were irrigated by central pivots for grain and silage, in the north-western side of São Paulo State, Brazil. For ET acquirements, the SAFER (Simple Algorithm For Evapotranspiration Retrieving) algorithm was applied to Landsat satellite images during growing seasons (GS) from March to August of 2010. Polynomial functions relating Kc and the accumulated degree-days (DDac) allowed the estimation of evapotranspiration under potential conditions (ETp). Adding data on reference evapotranspiration (ET0), precipitation (P), irrigation (I) and productivity (Yp), irrigation performances were assessed. The Relative Evapotranspiration (RET) ranged from 0.78 to 1.00 and the Water Deficit (WD) presented a maximum of 110 mm GS-1. The Relative Water Supply (RWS) with values from 1.1 to 1.4 indicated high drainage rates.

Hydro-gravimetry in West-Africa: First results from the Djougou (Benin) superconducting gravimeter

The increasing number of hydro-gravimetry studies proves the rising interest of the hydrology community toward this monitoring method. The accuracy of superconducting gravimeters (SG) potentially allows the retrieval of small water storage changes (WSC) down to a few millimeters of equivalent water thickness. However, the importance of corrections applied to SG data to achieve such a precision in gravity residuals should be recalled. The Djougou permanent gravity station presented in this paper and located in northern Benin, West-Africa, provides a good opportunity to review these considerations. This station is equipped since July 2010 with the superconducting gravimeter SG-060 aimed at deriving WSC at different time-scales, daily to inter-annual. In this area, WSC are (1) part of the control system for evapotranspiration (ET) process, a key variable of the West-African monsoon cycle and (2) the state variable for resource management, a critical issue in storage-poor hard rock basement contexts such as in northern Benin. The potential for deriving WSC from time-lapse gravity data partly depends on environmental features such as topography and the instrument shelter. Therefore, this issue is addressed first, with the background idea that such sensitivity analysis should be undertaken before setting up any new instrument. In Djougou, local topography is quite flat leading to a theoretical straightforward relationship between gravity changes and WSC, close to the standard Bouguer value. However, the shelter plays a significant masking role, which is the principal limitation to the retrieval of fast hydrological processes such as ET following a rain event. Several issues concerning classical gravity corrections are also addressed in the paper. These include gap-filling procedures during rain-events and drift estimates for short time series. Special attention is provided to atmospheric corrections, and different approaches are tested: a simple scalar admittance, a filtered scalar admittance, a frequency-dependent admittance and direct atmospheric loading calculations. It is shown that the physically based approach of direct loading calculations performs better in both residual minimization and ET retrieval. Moreover, non-local hydrological effects are investigated and account for about 20% of the gravity residuals. Finally, gravity residuals are briefly analyzed at two distinct time scales: rapid (up to a few days) and seasonal. At the rapid time-scale, it is shown that ET retrieval is hardly achievable given shelter size and state-of-the-art atmospheric corrections. Still, mean values retrieved from this study are in accordance with known values of potential ET and lateral flow. Direct comparison of gravity changes with hydrological data (neutron probe monitoring and water table levels) show some discrepancies, particularly for the hydrological year of 2011, for which all hydrological data show a deficit, but SG and FG5 data do not. This preliminary analysis both provides a basis and call for further hydro-gravity modeling, to comprehensively investigate the water-cycle at the Djougou station.

Impacts of the broadband albedo on actual evapotranspiration estimated by S-SEBI model over an agricultural area

Surface albedo and emissivity are essential variables in surface energy balance. In recent decades, several land surface energy models have used both surface broadband albedo and emissivity in order to achieve reliable evapotranspiration retrievals on a daily basis. Despite these improvements in surface energy models, we noticed an assumption that most studies make when using this framework. It assumes that the surface broadband albedo and emissivity can be estimated directly as a weighted average of spectral surface bi-directional reflectances, and as a weighted average of spectral surface emissivities retrieved at a given view angle, respectively. However, this approach does not take into account surface anisotropy, which is described by the Bi-directional Reflectance Distribution Function (BRDF) in the case of the surface albedo. In this paper, we analyze the influence that estimating land surface albedo directly from the surface reflectance (αREF) or through the BRDF integration (αBRDF) has on the estimation of energy balance components (net radiation, latent and sensible heat fluxes and evapotranspiration) by using the Simplified Surface Energy Balance Index (S-SEBI). To this end, in-situ data and remote sensing images acquisitioned at different view zenith angles (VZA) such as 0°, ±40° and ±57° by the Airborne Hyperspectral Scanner (AHS) over an agricultural area were used. Results show high variation in αREF depending on the VZA when compared to αBRDF, with the highest difference observed in the backward scattering direction along the hot spot region (RMSE of 0.11 and relative error of 65%). Net radiation gives relative errors from 6 to 17%, with the maximum error obtained in the images that include the hot spot effect, whereas significant changes are not observed in case of the ground heat flux and the evaporative fraction. However, sensible heat flux, latent heat flux and daily evapotranspiration show relative errors ranging between 23–39%, 6–18% and 5–15% respectively. In a future study, the influence of estimating surface emissivity directly from the average of spectral emissivities under a given view angle or using a hemispherical value will be analyzed.

Mapping daily evapotranspiration at field scales over rainfed and irrigated agricultural areas using remote sensing data fusion

Continuous monitoring of daily evapotranspiration (ET) at field scale can be achieved by combining thermal infrared remote sensing data information from multiple satellite platforms, given that no single sensor currently exists today with the required spatiotemporal resolution. Here, an integrated approach to field-scale ET mapping is described, combining multi-scale surface energy balance evaluations and a data fusion methodology, namely the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), to optimally exploit spatiotemporal characteristics of image datasets collected by the Landsat and Moderate resolution Imaging Spectroradiometer (MODIS) sensors, as well as geostationary platforms. Performance of this methodology is evaluated over adjacent irrigated and rainfed fields, since mixed conditions are the most challenging for data fusion procedures, and in two different climatic regions: a semi-arid site in Bushland, TX and a temperate site in Mead, NE. Daytime-total ET estimates obtained for the Landsat overpass dates suggest that the intrinsic model accuracy is consistent across the different test sites (and on the order of 0.5mmd−1) when contemporaneous Landsat imagery at 30-m resolution is available. Comparisons between tower observations and daily ET datastreams, reconstructed between overpasses by fusing Landsat and MODIS estimates, provide a means for assessing the strengths and limitations of the fused product. At the Mead site, the model performed similarly for both irrigated and rainfed fields, with an accuracy of about 0.9mmd−1. This similarity in performance is likely due to the relatively large size of the fields (≈50ha), suggesting that the soil moisture dynamics of the irrigated fields are reasonably well captured at the 1-km MODIS thermal pixel scale. On the other hand, the accuracy of daily retrievals for irrigated fields at the Bushland site was lower than that for the rainfed field (errors of 1.5 and 1.0mmd−1, respectively), likely due to the inability of the model to capture ET spikes right after irrigation events for fields substantially smaller than MODIS data resolution. At this site, the irrigated fields were small (≈5ha) compared to the MODIS pixel size, and sparsely distributed over the landscape, so sporadic contributions to ET from soil evaporation due to irrigation were not captured by the 1-km MODIS ET retrievals. However, due the semiarid environment at Bushland, these irrigation-induced spikes in soil evaporation are not long-lived and these underestimations generally affect the irrigation dates only and they do not seem to influence negatively the estimates at the seasonal scale. ET data fusion is expected to perform better over agricultural areas where irrigation is more spatially continuous, resulting in moisture fluxes that are more uniform at the MODIS pixel scale. Overall, the model accurately reproduces the ET temporal dynamics for all the experimental sites, and is able to capture the main differences that were observed between irrigated and rainfed fields at both daily and seasonal time scales.

Large-Scale Water Productivity Assessments with MODIS Images in a Changing Semi-Arid Environment: A Brazilian Case Study

In the Brazilian semi-arid region, the intensification of agriculture results in a change of natural vegetation by irrigated crops. To quantify the contrast between these two ecosystems, the large-scale values of water productivity components were modelled in Petrolina (PE) and Juazeiro (BA) municipalities. The SAFER (Simple Algorithm For Evapotranspiration Retrieving) algorithm was used to acquire evapotranspiration (ET), while the Monteith's radiation model was applied for estimating the biomass production (BIO). Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images were used together with agro-meteorological data. In Petrolina and Juazeiro, the mean monthly ET values for irrigated crops were 938 and 739 mm∙month−1, with the corresponding ones for natural vegetation of 385 and 194 mm∙month−1.Water productivity (WP) was analysed by the ratio of BIO to ET, defined here as the ratio of the net benefits from the mixed agricultural systems to the amount of water required for producing those benefits. The highest incremental WP values, as a result of the irrigated crops introduction, happened outside the rainy period. More spatial WP uniformity occurred in natural vegetation, when comparing with irrigated crops. The most frequent WP values in Petrolina were between 1.6 and 2.2 kg∙m−3 while in Juazeiro this range was from 1.0 to 1.6 kg∙m−3. The differences between the municipalities can be mainly explained by differences in precipitation and soil water storages conditions, promoting better rainfall use efficiency by the natural vegetation in the first one. The results of the current research are important for appraising the land use change impacts in situations of expanding irrigation areas.

Evaluation of the SEBS for upscaling the evapotranspiration based on in-situ observations over the Tibetan Plateau

Evapotranspiration (ET) is a boundary condition for regional scale hydrological and climatological modeling. Spatial knowledge of land surface ET is of principal interest for environmental evaluation especially in semi-arid regions. The study used the Surface Energy Balance System (SEBS) model based on Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) remote sensing and field observations data that have been used and tested for deriving ET over the NamCo area in the Tibetan Plateau, located in the southwest of China. Two ASTER scenes were used for estimating the ET over the study area. To validate the proposed methodology, the ground-measured ET was compared to the ASTER derived ET values for the study area. The results show that the derived ET in different months over the study area is in good accordance with the in-situ data. The derived ET value over the study area is much closer to the field measurement; the RMSE is 0.7mm/d. It is therefore concluded that the SEBS methodology is successful for the retrieval of ET using the ASTER and in-situ data over the study area.

English

Evapotranspiration (ET) is a major component in the water and heat balance of terrestrial ecosystems as well as in the water, energy and carbon cycles on the Earth’s surface. A growing number of studies have focused on the retrieval of ET from remote sensing (RS) data. However, the RS-derived ET results could not be validated by station-observed data directly for the difference of the scale. The objective of this study is to present an operational approach to validation of RS-derived ET under the support of a distributed hydrological model: soil and water assessment tool (SWAT). Five years (2000-2004) evapotranspiration data of Zhelin Basin, the study area, were prepared. RS-derived ET and other data (DEM, land-use data, soil data, etc) were processed together in SWAT to simulate the hydrological cycle. The output monthly runoff is compared with observed runoff data. The RS-derived ET was then validated based on the results of those comparison (R2=0.8516, RMSE=26.0860, MBE=-8.6578). It indicated that the method presented in the paper was an operational and feasible way for validation of ET data from remote sensing retrieval. Key words: Distributed hydrological model, evapotranspiration, remote sensing, soil and water assessment tool (SWAT).

Comparative assessment of evapotranspiration derived from NCEP and ECMWF global datasets through Weather Research and Forecasting model

AbstractIn many hydro‐meteorological applications, it is not always possible to get access to in situ weather measurements, especially for the ungauged catchments. This study explores the performances of downscaled weather data for Reference Evapotranspiration (ETo) retrieval using the global European Centre for Medium Range Weather Forecasts (ECMWF) ERA interim and National Centers for Environmental Prediction (NCEP) reanalysis data, simulated through Weather Research and Forecasting (WRF) mesoscale model. The range of the Nash‐Sutcliffe efficiency calculated for the ECMWF pooled datasets derived ETo varies from 0.31 to 0.87, while for NCEP it is found to be 0.11 to 0.38. Bias and Root Mean Square Error (RMSE) are also indicating a very high discrepancy in the NCEP ETo (Bias = −0.05; RMSE = 0.11) as compared to ECMWF (Bias = 0.00; RMSE = 0.06). The overall findings reveal that ECMWF downscaled products have a much better performance than the NCEP's counterparts. Copyright © 2013 Royal Meteorological Society

Reconstruction of temporal variations of evapotranspiration using instantaneous estimates at the time of satellite overpass

Abstract. Evapotranspiration estimates can be derived from remote sensing data and ancillary, mostly meterorological, information. For this purpose, two types of methods are classically used: the first type estimates a potential evapotranspiration rate from vegetation indices, and adjusts this rate according to water availability derived from either a surface temperature index or a first guess obtained from a rough estimate of the water budget, while the second family of methods relies on the link between the surface temperature and the latent heat flux through the surface energy budget. The latter provides an instantaneous estimate at the time of satellite overpass. In order to compute daily evapotranspiration, one needs an extrapolation algorithm. Since no image is acquired during cloudy conditions, these methods can only be applied during clear sky days. In order to derive seasonal evapotranspiration, one needs an interpolation method. Two combined interpolation/extrapolation methods based on the self preservation of evaporative fraction and the stress factor are compared to reconstruct seasonal evapotranspiration from instantaneous measurements acquired in clear sky conditions. Those measurements are taken from instantaneous latent heat flux from 11 datasets in Southern France and Morocco. Results show that both methods have comparable performances with a clear advantage for the evaporative fraction for datasets with several water stress events. Both interpolation algorithms tend to underestimate evapotranspiration due to the energy limiting conditions that prevail during cloudy days. Taking into account the diurnal variations of the evaporative fraction according to an empirical relationship derived from a previous study improved the performance of the extrapolation algorithm and therefore the retrieval of the seasonal evapotranspiration for all but one datasets.

Mapping daily evapotranspiration at Landsat spatial scales during the BEAREX’08 field campaign

Robust spatial information about environmental water use at field scales and daily to seasonal timesteps will benefit many applications in agriculture and water resource management. This information is particularly critical in arid climates where freshwater resources are limited or expensive, and groundwater supplies are being depleted at unsustainable rates to support irrigated agriculture as well as municipal and industrial uses. Gridded evapotranspiration (ET) information at field scales can be obtained periodically using land–surface temperature-based surface energy balance algorithms applied to moderate resolution satellite data from systems like Landsat, which collects thermal-band imagery every 16days at a resolution of approximately 100m. The challenge is in finding methods for interpolating between ET snapshots developed at the time of a clear-sky Landsat overpass to provide complete daily time-series over a growing season. This study examines the efficacy of a simple gap-filling algorithm designed for applications in data-sparse regions, which does not require local ground measurements of weather or rainfall, or estimates of soil texture. The algorithm relies on general conservation of the ratio between actual ET and a reference ET, generated from satellite insolation data and standard meteorological fields from a mesoscale model. The algorithm was tested with ET retrievals from the Atmosphere–Land Exchange Inverse (ALEXI) surface energy balance model and associated DisALEXI flux disaggregation technique, which uses Landsat-scale thermal imagery to reduce regional ALEXI maps to a finer spatial resolution. Daily ET at the Landsat scale was compared with lysimeter and eddy covariance flux measurements collected during the Bushland Evapotranspiration and Agricultural Remote sensing EXperiment of 2008 (BEAREX08), conducted in an irrigated agricultural area in the Texas Panhandle under highly advective conditions. The simple gap-filling algorithm performed reasonably at most sites, reproducing observed cumulative ET to within 5–10% over the growing period from emergence to peak biomass in both rainfed and irrigated fields.

Estimating evapotranspiration using an observation based terrestrial water budget

ABSTRACTEvapotranspiration (ET) is difficult to measure at the scales of climate models and climate variability. While satellite retrieval algorithms do exist, their accuracy is limited by the sparseness of in situ observations available for calibration and validation, which themselves may be unrepresentative of 500 m and larger scale satellite footprints and grid pixels. Here, we use a combination of satellite and ground‐based observations to close the water budgets of seven continental scale river basins (Mackenzie, Fraser, Nelson, Mississippi, Tocantins, Danube, and Ubangi), estimating mean ET as a residual. For any river basin, ET must equal total precipitation minus net runoff minus the change in total terrestrial water storage (TWS), in order for mass to be conserved. We make use of precipitation from two global observation‐based products, archived runoff data, and TWS changes from the Gravity Recovery and Climate Experiment (GRACE) satellite mission. We demonstrate that while uncertainty in the water budget‐based estimates of monthly ET is often too large for those estimates to be useful, the uncertainty in the mean annual cycle is small enough that it is practical for evaluating other ET products. Here, we evaluate five land surface model simulations, two operational atmospheric analyses, and a recent global reanalysis product based on our results. An important outcome is that the water budget‐based ET time series in two tropical river basins, one in Brazil and the other in central Africa, exhibit a weak annual cycle, which may help to resolve debate about the strength of the annual cycle of ET in such regions and how ET is constrained throughout the year. The methods described will be useful for water and energy budget studies, weather and climate model assessments, and satellite‐based ET retrieval optimization. Copyright © 2011 John Wiley & Sons, Ltd.

Evapotranspiration information reporting: I. Factors governing measurement accuracy

Abstract More and more evapotranspiration models, evapotranspiration crop coefficients and associated measurements of evapotranspiration (ET) are being reported in the literature and used to develop, calibrate and test important ET process models. ET data are derived from a range of measurement systems including lysimeters, eddy covariance, Bowen ratio, water balance (gravimetric, neutron meter, other soil water sensing), sap flow, scintillometry and even satellite-based remote sensing and direct modeling. All of these measurement techniques require substantial experimental care and are prone to substantial biases in reported results. Reporting of data containing measurement biases causes substantial confusion and impedance to the advancement of ET models and in the establishment of irrigation water requirements, and translates into substantial economic losses caused by misinformed water management. Basic principles of ET measuring systems are reviewed and causes of common error and biases endemic to systems are discussed. Recommendations are given for reducing error in ET retrievals. Upper limits on ET measurements and derived crop coefficients are proposed to serve as guidelines. The descriptions of errors common to measurement systems are intended to help practitioners collect better data as well as to assist reviewers of manuscripts and users of data and derived products in assessing quality, integrity, validity and representativeness of reported information. This paper is the first part of a two-part series, where the second part describes recommendations for documentation to be associated with published ET data.

An integrated model of soil-canopy spectral radiances, photosynthesis, fluorescence, temperature and energy balance

Abstract. This paper presents the model SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes), which is a vertical (1-D) integrated radiative transfer and energy balance model. The model links visible to thermal infrared radiance spectra (0.4 to 50 μm) as observed above the canopy to the fluxes of water, heat and carbon dioxide, as a function of vegetation structure, and the vertical profiles of temperature. Output of the model is the spectrum of outgoing radiation in the viewing direction and the turbulent heat fluxes, photosynthesis and chlorophyll fluorescence. A special routine is dedicated to the calculation of photosynthesis rate and chlorophyll fluorescence at the leaf level as a function of net radiation and leaf temperature. The fluorescence contributions from individual leaves are integrated over the canopy layer to calculate top-of-canopy fluorescence. The calculation of radiative transfer and the energy balance is fully integrated, allowing for feedback between leaf temperatures, leaf chlorophyll fluorescence and radiative fluxes. Leaf temperatures are calculated on the basis of energy balance closure. Model simulations were evaluated against observations reported in the literature and against data collected during field campaigns. These evaluations showed that SCOPE is able to reproduce realistic radiance spectra, directional radiance and energy balance fluxes. The model may be applied for the design of algorithms for the retrieval of evapotranspiration from optical and thermal earth observation data, for validation of existing methods to monitor vegetation functioning, to help interpret canopy fluorescence measurements, and to study the relationships between synoptic observations with diurnally integrated quantities. The model has been implemented in Matlab and has a modular design, thus allowing for great flexibility and scalability.