Global patterns of annual actual evapotranspiration with land-cover type: knowledge gained from a new observation-based database

Abstract

The process of evapotranspiration (ET) plays a critical role in the earth system, driving key land-surface processes in the energy, water and carbon cycles. Land-cover (LC) exerts multiple controls on ET, yet the global distribution of ET by LC and the related physical variables are poorly understood. The lack of quantitative understanding of global ET variation with LC begets considerable uncertainties regarding how ET and key land-surface processes will change alongside ongoing anthropogenic LC transformations. Here we apply statistical analysis and models to a new global ET database to advance our understanding of how annual actual ET varies with LC type. We derive global fields for each LC using linear mixed effect models (LMMs) that use geographical and meteorological variables as possible independent regression variables. Our inventory of ET observations reveals important gaps in spatial coverage that overlie hotpots of global change. There is a spatial bias of observations towards the mid latitudes, and LCs with large areas in the high latitudes (lakes, wetlands and barren land) are poorly represented. From the distribution of points as well as the uncertainty analysis completed by bootstrapping we identify high priority regions in need of more data collection. Our analysis of the new database provides new insights into how ET varies globally, providing more robust estimates of global ET rates for a broad range of LC types. Results reveal that different LC types have distinct global patterns of ET. Furthermore, zonal ET means among LCs reveal new patterns: ET rates in low latitudinal bands are more sensitive to LC change than in higher latitude bands; LCs with a higher evaporation component show higher variability of ET at the global scale; and LCs with dispersed rather than contiguous global locations have a higher variability of ET at the global scale. Results from this study indicate two major advancements are required to improve our ability to predict how ET will vary with global change. First, further collection of ground truth observations of ET is needed to fill gaps in LC types and spatial location identified in this paper. Second, LC types need to be de-aggregated into finer categories to better characterize ET, to reduce uncertainty and weakened strength to predictor variables, associated by aggregation of heterogeneous LC types into one group; this will require the development of higher-resolution LC databases.