Multi-site evaluation of terrestrial evaporation models using FLUXNET data
KAUST DepartmentWater Desalination and Reuse Research Center (WDRC)
Biological and Environmental Sciences and Engineering (BESE) Division
Environmental Science and Engineering Program
Earth System Observation and Modelling
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AbstractWe evaluated the performance of four commonly applied land surface evaporation models using a high-quality dataset of selected FLUXNET towers. The models that were examined include an energy balance approach (Surface Energy Balance System; SEBS), a combination-type technique (single-source Penman-Monteith; PM), a complementary method (advection-aridity; AA) and a radiation based approach (modified Priestley-Taylor; PT-JPL). Twenty FLUXNET towers were selected based upon satisfying stringent forcing data requirements and representing a wide range of biomes. These towers encompassed a number of grassland, cropland, shrubland, evergreen needleleaf forest and deciduous broadleaf forest sites. Based on the mean value of the Nash-Sutcliffe efficiency (NSE) and the root mean squared difference (RMSD), the order of overall performance of the models from best to worst were: ensemble mean of models (0.61, 64), PT-JPL (0.59, 66), SEBS (0.42, 84), PM (0.26, 105) and AA (0.18, 105) [statistics stated as (NSE, RMSD in Wm-2)]. Although PT-JPL uses a relatively simple and largely empirical formulation of the evaporative process, the technique showed improved performance compared to PM, possibly due to its partitioning of total evaporation (canopy transpiration, soil evaporation, wet canopy evaporation) and lower uncertainties in the required forcing data. The SEBS model showed low performance over tall and heterogeneous canopies, which was likely a consequence of the effects of the roughness sub-layer parameterization employed in this scheme. However, SEBS performed well overall. Relative to PT-JPL and SEBS, the PM and AA showed low performance over the majority of sites, due to their sensitivity to the parameterization of resistances. Importantly, it should be noted that no single model was consistently best across all biomes. Indeed, this outcome highlights the need for further evaluation of each model's structure and parameterizations to identify sensitivities and their appropriate application to different surface types and conditions. It is expected that the results of this study can be used to inform decisions regarding model choice for water resources and agricultural management, as well as providing insight into model selection for global flux monitoring efforts. © 2013 Elsevier B.V.
SponsorsFunding for this research was provided via an Australian Research Council (ARC) Linkage (LP0989441) and Discovery (DP120104718) project, together with a top-up scholarship to support Ali Ershadi from the National Centre for Groundwater Research and Training (NCGRT) in Australia. We thank the FLUXNET site investigators for allowing us to use their meteorological data. This work used eddy covariance data acquired by the FLUXNET community and in particular by the Ameri-Flux (U.S. Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program: DE-FG02-04ER63917 and DE-FG02-04ER63911) and OzFlux. We acknowledge the financial support to the eddy covariance data harmonization provided by CarboEuropeIP, FAO-GTOS-TCO,iLEAPS, Max Planck Institute for Biogeochemistry, National Science Foundation, University of Tuscia, Universite Laval and Environment Canada and US Department of Energy and the database development and technical support from Berkeley Water Center, Lawrence Berkeley National Laboratory, Microsoft Research eScience, Oak Ridge National Laboratory, University of California - Berkeley, University of Virginia. Data supplied by T. Kolb, School of Forestry, Northern Arizona University, for the US-Fuf site was supported by grants from the North American Carbon Program/USDA NRI (2004-35111-15057; 2008-35101-19076), Science Foundation Arizona (CAA 0-203-08) and the Arizona Water Institute. Matlab scripts for automatic downloading of MOD13Q1 data were provided by Dr Tristan Quaife, University College London via the web portal at http://daac.ornl.gov/MODIS/MODIS-menu/modis_webservice.html. We acknowledge the contributions provided via the LandFlux-EVAL initiative and the WACMOS ET project.