scholarly journals Comparison of different evaporation estimates over the African continent

2013 ◽  
Vol 10 (7) ◽  
pp. 8421-8465 ◽  
Author(s):  
P. Trambauer ◽  
E. Dutra ◽  
S. Maskey ◽  
M. Werner ◽  
F. Pappenberger ◽  
...  
Keyword(s):  
Land Surface ◽  
Hydrological Model ◽  
Regional Scale ◽  
African Continent ◽  
Land Surface Models ◽  
Continental Scale ◽  
Actual Evaporation ◽  
Balance Approach ◽  
Surface Models ◽  
Energy Balance Approach

Abstract. Evaporation is a key process in the water cycle, with implications ranging from water management, to weather forecast and climate change assessments. The estimation of continental evaporation fluxes is complex and typically relies on continental-scale hydrological or land-surface models. However, it appears that most global or continental-scale hydrological models underestimate evaporative fluxes in some regions of Africa, and as a result overestimate stream flow. Other studies suggest that land-surface models may overestimate evaporative fluxes. In this study, we computed actual evaporation for the African continent using a continental version of the global hydrological model PCR-GLOBWB, which is based on a water balance approach. Results are compared with other independently computed evaporation products: the evaporation results from the ECMWF reanalysis ERA-Interim and ERA-Land (both based on the energy balance approach), the MOD16 evaporation product, and the GLEAM product. Three other alternative versions of the PCR-GLOBWB hydrological model were also considered. This resulted in eight products of actual evaporation, which were compared in distinct regions of the African continent spanning different climatic regimes. Annual totals, spatial patterns and seasonality were studied and compared through visual inspection and statistical methods. The comparison shows that the representation of irrigation areas has an insignificant contribution to the actual evaporation at a continental scale with a 0.5° spatial resolution. The choice of meteorological forcing data has a larger effect on the evaporation results, especially in the case of the precipitation input as different precipitation input resulted in significantly different evaporation in some of the studied regions. ERA-Interim evaporation is generally the highest of the selected products followed by ERA-Land evaporation. The satellite based products (GLEAM and MOD16) do not show regular behaviour when compared to the other products, though this depends on the region and the season considered. The results from this study allow for a better understanding of the differences between products in each climatic region. Through an improved understanding of the causes of differences between these products and their uncertainty, this study provides information to improve the quality of evaporation products for the African continent and, consequently, leads to improved water resources assessments at regional scale.

scholarly journals Comparison of different evaporation estimates over the African continent

2014 ◽  
Vol 18 (1) ◽  
pp. 193-212 ◽  
Author(s):  
P. Trambauer ◽  
E. Dutra ◽  
S. Maskey ◽  
M. Werner ◽  
F. Pappenberger ◽  
...  
Keyword(s):  
Land Surface ◽  
Hydrological Model ◽  
Hydrological Models ◽  
African Continent ◽  
Land Surface Models ◽  
Continental Scale ◽  
Actual Evaporation ◽  
Balance Approach ◽  
Surface Models ◽  
Energy Balance Approach

Abstract. Evaporation is a key process in the water cycle with implications ranging, inter alia, from water management to weather forecast and climate change assessments. The estimation of continental evaporation fluxes is complex and typically relies on continental-scale hydrological models or land-surface models. However, it appears that most global or continental-scale hydrological models underestimate evaporative fluxes in some regions of Africa, and as a result overestimate stream flow. Other studies suggest that land-surface models may overestimate evaporative fluxes. In this study, we computed actual evaporation for the African continent using a continental version of the global hydrological model PCR-GLOBWB, which is based on a water balance approach. Results are compared with other independently computed evaporation products: the evaporation results from the ECMWF reanalysis ERA-Interim and ERA-Land (both based on the energy balance approach), the MOD16 evaporation product, and the GLEAM product. Three other alternative versions of the PCR-GLOBWB hydrological model were also considered. This resulted in eight products of actual evaporation, which were compared in distinct regions of the African continent spanning different climatic regimes. Annual totals, spatial patterns and seasonality were studied and compared through visual inspection and statistical methods. The comparison shows that the representation of irrigation areas has an insignificant contribution to the actual evaporation at a continental scale with a 0.5° spatial resolution when averaged over the defined regions. The choice of meteorological forcing data has a larger effect on the evaporation results, especially in the case of the precipitation input as different precipitation input resulted in significantly different evaporation in some of the studied regions. ERA-Interim evaporation is generally the highest of the selected products followed by ERA-Land evaporation. In some regions, the satellite-based products (GLEAM and MOD16) show a different seasonal behaviour compared to the other products. The results from this study contribute to a better understanding of the suitability and the differences between products in each climatic region. Through an improved understanding of the causes of differences between these products and their uncertainty, this study provides information to improve the quality of evaporation products for the African continent and, consequently, leads to improved water resources assessments at regional scale.

scholarly journals Multimodel Estimate of the Global Terrestrial Water Balance: Setup and First Results

2011 ◽  
Vol 12 (5) ◽  
pp. 869-884 ◽  
Author(s):  
Ingjerd Haddeland ◽  
Douglas B. Clark ◽  
Wietse Franssen ◽  
Fulco Ludwig ◽  
Frank Voß ◽  
...  
Keyword(s):  
Water Balance ◽  
Land Surface ◽  
Water Model ◽  
Hydrological Models ◽  
Model Intercomparison ◽  
Land Surface Models ◽  
Surface Models ◽  
Terrestrial Water ◽  
Intercomparison Project ◽  
Energy Balance Approach

Abstract Six land surface models and five global hydrological models participate in a model intercomparison project [Water Model Intercomparison Project (WaterMIP)], which for the first time compares simulation results of these different classes of models in a consistent way. In this paper, the simulation setup is described and aspects of the multimodel global terrestrial water balance are presented. All models were run at 0.5° spatial resolution for the global land areas for a 15-yr period (1985–99) using a newly developed global meteorological dataset. Simulated global terrestrial evapotranspiration, excluding Greenland and Antarctica, ranges from 415 to 586 mm yr−1 (from 60 000 to 85 000 km3 yr−1), and simulated runoff ranges from 290 to 457 mm yr−1 (from 42 000 to 66 000 km3 yr−1). Both the mean and median runoff fractions for the land surface models are lower than those of the global hydrological models, although the range is wider. Significant simulation differences between land surface and global hydrological models are found to be caused by the snow scheme employed. The physically based energy balance approach used by land surface models generally results in lower snow water equivalent values than the conceptual degree-day approach used by global hydrological models. Some differences in simulated runoff and evapotranspiration are explained by model parameterizations, although the processes included and parameterizations used are not distinct to either land surface models or global hydrological models. The results show that differences between models are a major source of uncertainty. Climate change impact studies thus need to use not only multiple climate models but also some other measure of uncertainty (e.g., multiple impact models).

scholarly journals Modeling Evapotranspiration over China’s Landmass from 1979 to 2012 Using Multiple Land Surface Models: Evaluations and Analyses

2017 ◽  
Vol 18 (4) ◽  
pp. 1185-1203 ◽  
Author(s):  
Shaobo Sun ◽  
Baozhang Chen ◽  
Quanqin Shao ◽  
Jing Chen ◽  
Jiyuan Liu ◽  
...  
Keyword(s):  
Land Surface ◽  
Regional Scale ◽  
Temporal Variations ◽  
The Tibetan Plateau ◽  
Land Surface Models ◽  
Infiltration Capacity ◽  
Community Land Model ◽  
Variable Infiltration Capacity Model ◽  
Capacity Model ◽  
Surface Models

Abstract Land surface models (LSMs) are useful tools to estimate land evapotranspiration at a grid scale and for long-term applications. Here, the Community Land Model, version 4.0 (CLM4.0); Dynamic Land Model (DLM); and Variable Infiltration Capacity model (VIC) were driven with observation-based forcing datasets, and a multiple-LSM ensemble-averaged evapotranspiration (ET) product (LSMs-ET) was developed and its spatial–temporal variations were analyzed for the China landmass over the period 1979–2012. Evaluations against measurements from nine flux towers at site scale and surface water budget–based ET at regional scale showed that the LSMs-ET had good performance in most areas of China’s landmass. The intercomparisons between the ET estimates and the independent ET products from remote sensing and upscaling methods suggested that there were fairly consistent patterns between each dataset. The LSMs-ET produced a mean annual ET of 351.24 ± 10.7 mm yr−1 over 1979–2012, and its spatial–temporal variation analyses showed that (i) there was an overall significant ET increasing trend, with a value of 0.72 mm yr−1 (p < 0.01), and (ii) 36.01% of Chinese land had significant increasing trends, ranging from 1 to 9 mm yr−1, while only 6.41% of the area showed significant decreasing trends, ranging from −6.28 to −0.08 mm yr−1. Analyses of ET variations in each climate region clearly showed that the Tibetan Plateau areas were the main contributors to the overall increasing ET trends of China.

scholarly journals MPR 1.0: A stand-alone Multiscale Parameter Regionalization Tool for Improved Parameter Estimation of Land Surface Models

2021 ◽  
Author(s):  
Robert Schweppe ◽  
Stephan Thober ◽  
Matthias Kelbling ◽  
Rohini Kumar ◽  
Sabine Attinger ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Parameter Space ◽  
Land Surface ◽  
Hydrologic Model ◽  
Model Parameters ◽  
Land Surface Models ◽  
Continental Scale ◽  
Environmental Models ◽  
Surface Models

Abstract. Distributed environmental models such as land surface models (LSM) require model parameters in each spatial modelling unit (e.g. grid cell), thereby leading to a high-dimensional parameter space. One approach to decrease the dimen- sionality of parameter space in these models is to use regularization techniques. One such highly efficient technique is the Multiscale Parameter Regionalization (MPR) framework that translates high-resolution predictor variables (e.g., soil textural properties) into model parameters (e.g., porosity) via transfer functions (TFs) and upscaling operators that are suitable for every modeled process. This framework yields seamless model parameters at multiple scales and locations in an effective manner. However, integration of MPR into existing modeling workflows has been hindered thus far by hard-coded configurations and non-modular software designs. For these reasons, we redesigned MPR as a model-agnostic, stand-alone tool. It is a useful software for creating graphs of netCDF variables, wherein each node is a variable and the links consist of TFs and/or upscaling operators. In this study, we present and verify our tool against a previous version, which was implemented in the mesoscale hydrologic model mHM (www.ufz.de/mhm). By using this tool for the generation of continental-scale soil hydraulic param- eters applicable to different models (Noah-MP and HTESSEL), we showcase its general functionality and flexibility. Further, using model parameters estimated by the MPR tool leads to significant changes in long-term estimates of evapotranspiration, as compared to their default parameterizations. For example, a change of up to 25 % in long-term evapotranspiration flux is observed in Noah-MP and HTESSEL in the Mississippi River basin. We postulate that use of the stand-alone MPR tool will considerably increase the transparency and reproducibility of the parameter estimation process in distributed (environmental) models. It will also allow a rigorous uncertainty estimation related to the errors of the predictors (e.g., soil texture fields), transfer function and its parameters, and remapping (or upscaling) algorithms.

scholarly journals Modeling sugar cane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values

2014 ◽  
Vol 7 (1) ◽  
pp. 1197-1244
Author(s):  
A. Valade ◽  
P. Ciais ◽  
N. Vuichard ◽  
N. Viovy ◽  
N. Huth ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Sugar Cane ◽  
Land Surface ◽  
Cane Yield ◽  
Land Surface Models ◽  
Continental Scale ◽  
Surface Models ◽  
Input Parameters ◽  
Parameter Values ◽  
Sensitive Parameters

Abstract. Agro-Land Surface Models (agro-LSM) have been developed from the integration of specific crop processes into large-scale generic land surface models that allow calculating the spatial distribution and variability of energy, water and carbon fluxes within the soil-vegetation-atmosphere continuum. When developing agro-LSM models, a particular attention must be given to the effects of crop phenology and management on the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty of Agro-LSM models is related to their usually large number of parameters. In this study, we quantify the parameter-values uncertainty in the simulation of sugar cane biomass production with the agro-LSM ORCHIDEE-STICS, using a multi-regional approach with data from sites in Australia, La Réunion and Brazil. In ORCHIDEE-STICS, two models are chained: STICS, an agronomy model that calculates phenology and management, and ORCHIDEE, a land surface model that calculates biomass and other ecosystem variables forced by STICS' phenology. First, the parameters that dominate the uncertainty of simulated biomass at harvest date are determined through a screening of 67 different parameters of both STICS and ORCHIDEE on a multi-site basis. Secondly, the uncertainty of harvested biomass attributable to those most sensitive parameters is quantified and specifically attributed to either STICS (phenology, management) or to ORCHIDEE (other ecosystem variables including biomass) through distinct Monte-Carlo runs. The uncertainty on parameter values is constrained using observations by calibrating the model independently at seven sites. In a third step, a sensitivity analysis is carried out by varying the most sensitive parameters to investigate their effects at continental scale. A Monte-Carlo sampling method associated with the calculation of Partial Ranked Correlation Coefficients is used to quantify the sensitivity of harvested biomass to input parameters on a continental scale across the large regions of intensive sugar cane cultivation in Australia and Brazil. Ten parameters driving most of the uncertainty in the ORCHIDEE-STICS modeled biomass at the 7 sites are identified by the screening procedure. We found that the 10 most sensitive parameters control phenology (maximum rate of increase of LAI) and root uptake of water and nitrogen (root profile and root growth rate, nitrogen stress threshold) in STICS, and photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), and transpiration and respiration (stomatal conductance, growth and maintenance respiration coefficients) in ORCHIDEE. We find that the optimal carboxylation rate and photosynthesis temperature parameters contribute most to the uncertainty in harvested biomass simulations at site scale. The spatial variation of the ranked correlation between input parameters and modeled biomass at harvest is well explained by rain and temperature drivers, suggesting climate-mediated different sensitivities of modeled sugar cane yield to the model parameters, for Australia and Brazil. This study reveals the spatial and temporal patterns of uncertainty variability for a highly parameterized agro-LSM and calls for more systematic uncertainty analyses of such models.

scholarly journals Modeling sugarcane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values

2014 ◽  
Vol 7 (3) ◽  
pp. 1225-1245 ◽  
Author(s):  
A. Valade ◽  
P. Ciais ◽  
N. Vuichard ◽  
N. Viovy ◽  
A. Caubel ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Land Surface ◽  
Surface Model ◽  
Land Surface Models ◽  
Continental Scale ◽  
Surface Models ◽  
Input Parameters ◽  
Sugarcane Yield ◽  
Parameter Values ◽  
Sensitive Parameters

Abstract. Agro-land surface models (agro-LSM) have been developed from the integration of specific crop processes into large-scale generic land surface models that allow calculating the spatial distribution and variability of energy, water and carbon fluxes within the soil–vegetation–atmosphere continuum. When developing agro-LSM models, particular attention must be given to the effects of crop phenology and management on the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty of agro-LSM models is related to their usually large number of parameters. In this study, we quantify the parameter-values uncertainty in the simulation of sugarcane biomass production with the agro-LSM ORCHIDEE–STICS, using a multi-regional approach with data from sites in Australia, La Réunion and Brazil. In ORCHIDEE–STICS, two models are chained: STICS, an agronomy model that calculates phenology and management, and ORCHIDEE, a land surface model that calculates biomass and other ecosystem variables forced by STICS phenology. First, the parameters that dominate the uncertainty of simulated biomass at harvest date are determined through a screening of 67 different parameters of both STICS and ORCHIDEE on a multi-site basis. Secondly, the uncertainty of harvested biomass attributable to those most sensitive parameters is quantified and specifically attributed to either STICS (phenology, management) or to ORCHIDEE (other ecosystem variables including biomass) through distinct Monte Carlo runs. The uncertainty on parameter values is constrained using observations by calibrating the model independently at seven sites. In a third step, a sensitivity analysis is carried out by varying the most sensitive parameters to investigate their effects at continental scale. A Monte Carlo sampling method associated with the calculation of partial ranked correlation coefficients is used to quantify the sensitivity of harvested biomass to input parameters on a continental scale across the large regions of intensive sugarcane cultivation in Australia and Brazil. The ten parameters driving most of the uncertainty in the ORCHIDEE–STICS modeled biomass at the 7 sites are identified by the screening procedure. We found that the 10 most sensitive parameters control phenology (maximum rate of increase of LAI) and root uptake of water and nitrogen (root profile and root growth rate, nitrogen stress threshold) in STICS, and photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), and transpiration and respiration (stomatal conductance, growth and maintenance respiration coefficients) in ORCHIDEE. We find that the optimal carboxylation rate and photosynthesis temperature parameters contribute most to the uncertainty in harvested biomass simulations at site scale. The spatial variation of the ranked correlation between input parameters and modeled biomass at harvest is well explained by rain and temperature drivers, suggesting different climate-mediated sensitivities of modeled sugarcane yield to the model parameters, for Australia and Brazil. This study reveals the spatial and temporal patterns of uncertainty variability for a highly parameterized agro-LSM and calls for more systematic uncertainty analyses of such models.

scholarly journals Improving evapotranspiration in land surface models by using biophysical parameters derived from MSG/SEVIRI satellite

2011 ◽  
Vol 8 (5) ◽  
pp. 9113-9171 ◽  
Author(s):  
N. Ghilain ◽  
A. Arboleda ◽  
G. Sepulcre-Cantò ◽  
O. Batelaan ◽  
J. Ardö ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Surface Model ◽  
Spatial And Temporal Variability ◽  
Land Surface Models ◽  
Area Index ◽  
Continental Scale ◽  
Surface Models ◽  
Vegetation Parameters ◽  
The Impact

Abstract. Vegetation parameters derived from the geostationary satellite MSG/SEVIRI have been distributed at a daily frequency since 2007 over Europe, Africa and part of South America, through the LSA-SAF facility. We propose here a method to handle two new remote sensing products from LSA-SAF, leaf area index and Fractional Vegetation Cover, noted LAI and FVC respectively, for land surface models at MSG/SEVIRI scale. The developed method relies on an ordinary least-square technique and a land cover map to estimate LAI for each model plant functional types of the model spatial unit. The method is conceived to be applicable for near-real time applications at continental scale. Compared to monthly vegetation parameters from a vegetation database commonly used in numerical weather predictions (ECOCLIMAP-I), the new remote sensing products allows a better monitoring of the spatial and temporal variability of the vegetation, including inter-annual signals, and a decreased uncertainty on LAI to be input into land surface models. We assess the impact of using LSA-SAF vegetation parameters compared to ECOCLIMAP-I in the land surface model H-TESSEL at MSG/SEVIRI scale. Comparison with in-situ observations in Europe and Africa shows that the results on evapotranspiration are mostly improved, and especially in semi-arid climates. At last, the use of LSA-SAF and ECOCLIMAP-I is compared with simulations over a North-South Transect in Western Africa using LSA-SAF radiation forcing derived from remote sensing, and differences are highlighted.

Evaluating Validity of Bouchet-Morton Complementary Relationship at Regional Scale through Terrestrial Evapotranspiration derived using Remote Sensing Platform and Land Surface Models

2020 ◽  
Author(s):  
Swapan Kumar Masanta ◽  
Srinivas Venkata Vemavarapu
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Regional Scale ◽  
Climate Variables ◽  
Land Surface Models ◽  
Complementary Relationship ◽  
Surface Models ◽  
Clustering Approach ◽  
Possible Cause ◽  
Vegetation And Climate

<p>Evapotranspiration is one of the most important components of the terrestrial hydrological cycle, which depicts atmospheric water demand and accounts for loss of more than 60% land-surface precipitation globally. Decrease in potential/reference evapotranspiration (ET<sub>p</sub>), despite significant increase in near-surface air temperature is reported at many locations across the world in the recent decades. This counter-intuitive phenomenon known as evaporation-paradox could be attributed to decrease in net solar radiation and/or wind speed and/or increase in terrestrial evapotranspiration (ET<sub>a</sub>). Gaining insight into evaporation-paradox requires understanding complex interaction between land-plant-atmosphere systems. Bouchet–Morton complementary relationship (CR) hypothesizes that at regional scale there exists a feedback mechanism between ET<sub>a</sub> and ET<sub>p</sub> for homogeneous surfaces having low advection of heat and moisture. It postulates that increase in regional ET<sub>a</sub> consumes energy thereby cooling and humidifying the overpassing air, which would result in reduction of regional ET<sub>p</sub>. Similarly, available excess energy which is not used for evapotranspiration (due to decrease in regional ET<sub>a</sub>) would result in an increase of regional ET<sub>p</sub> through warming and drying of the atmosphere. Recent improvements in remote sensing technology provide scope to quantify ET<sub>a</sub> and use it for evaluating validity of CR at regional scale to discern the possible cause for evaporation-paradox. If the CR is valid for a region, models could be developed to estimate regional ET<sub>a</sub> using ET<sub>p</sub> estimated using regional values of its predictor hydro-climate variables. Prior studies on Indian subcontinent found evidence of evaporation-paradox at various sites scattered widely in space. But there is lack of attempts to establish existence of the paradox at regional scale and discern possible cause(s) for the same. In this backdrop, research is envisaged to (i) form homogeneous ET<sub>a</sub> and ET<sub>p</sub> regions in India using a novel dynamic fuzzy clustering approach, (ii) investigate existence of evaporation-paradox in each of those regions, and (iii) identify validity of CR and discern possible cause(s) for the paradox, if evident. ET<sub>a</sub> is typically estimated from eddy covariance flux towers, remote sensing techniques, or computed from land surface models which often suffer from limitations of scale and data. Uncertainty arising due to the use of (i) two different hydro-climate re-analysis datasets for ET<sub>p</sub> estimation, and (ii) one remote sensing based and three land surface model derived ET<sub>a</sub> products is assessed. The dynamic clustering approach yielded 18 homogeneous ET<sub>p</sub> regions and 30 homogeneous ET<sub>a</sub> regions in India. The role of CR on evaporation-paradox was evident in eight regions. The effect of vegetation and climate on CR is studied at regional scale using NDVI (normalized difference vegetation index). In addition, existence of CR hypotheses is verified in 405 major river basins of different sizes located in diverse climate regions across the globe using combination of several model derived and remotely sensed ET<sub>a</sub> and ET<sub>p</sub> datasets. This study is of significance, as evidence of the effect of location, vegetation and climate on CR at regional scale gives scope for developing region-specific models to arrive at ET<sub>a</sub> estimates directly from ET<sub>p</sub> which could be estimated/forecasted from hydro-climate variables.</p>

scholarly journals Inter-comparison of energy balance and hydrological models for land surface energy fluxes estimation over a whole river catchment

2014 ◽  
Vol 11 (6) ◽  
pp. 5905-5951 ◽  
Author(s):  
R. Guzinski ◽  
H. Nieto ◽  
S. Stisen ◽  
R. Fensholt
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Water Balance ◽  
Land Surface ◽  
Hydrological Model ◽  
Area Index ◽  
Mike She ◽  
River Catchment ◽  
Balance Approach ◽  
Energy Balance Approach

Abstract. Evapotranspiration is the main link between the natural water cycle and the land surface energy budget. Therefore water-balance and energy-balance approaches are two of the main methodologies for modelling of this process. The water-balance approach ensures that the amount of water coming into a system, mainly through precipitation, is balanced by the amount of water leaving the system through evapotranspiration, runoff and other processes. This modelling methodology is usually implemented as a complex, distributed hydrological model. The energy-balance approach ensures the conservation of energy at the land surface and is often used with remotely sensed observations of, for example, the land surface temperature (LST) and the state of the vegetation. In this study we compare the catchment scale output of two remote sensing models based on the Two-Source Energy Balance (TSEB) scheme, against a hydrological model, MIKE SHE, calibrated over the Skjern river catchment in western Denmark, the area covered by the Danish Hydrological Observatory (HOBE). The first TSEB model utilizes the time differential LST measurements provided by the night and day overpasses of the MODIS sensor aboard the Aqua satellite, while the second uses the dual-angle LST measurements made available by the AATSR sensor that used to fly on the Envisat satellite. All three models use the same ancillary data (meteorological measurements, land cover type and leaf area index, etc.) and produce output at similar spatial resolution (1 km for the TSEB models, 500 m for MIKE SHE). The comparison is performed on the spatial patterns of the fluxes present within the catchment area as well as on temporal patterns visible in 7 year long time series. The results aid the understanding of strengths and weaknesses of each modelling approach and explore the benefits to the hydrological modelling community of evapotranspiration maps derived with the energy-balance methodology.

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