Evapotranspiration (ET) is the key water flux at the interface of soil, vegetation and atmosphere. ET is difficult to measure directly; therefore, a range of methods have been developed within different research disciplines to estimate ET.

Remote sensing datasets are increasingly being used to provide spatially-explicit, large-scale ET estimates. While satellite datasets have been used to estimate basin- to field-scale ET, aerial platforms such as UAVs and drones are becoming popular for field-scale studies. These datasets, in combination with micrometeorological data, can be used to produce empirical models for improving ET estimates at larger scales. However, the uncertainty in ET that varies by the datasets which are used, hydro-climatic region, spatiotemporal scale, and modelling approaches, is not well understood.

Additionally, there is a range of in-situ methods such as lysimeters, sap flow, eddy covariance, scintillometers and Bowen ratio to estimate ET from ground-based measurements. However, estimating and scaling in-situ ET is prone to large method-specific uncertainties which are rarely communicated across different disciplines. This is problematic if in-situ measurements are to be compared, combined or scaled up to match the grid resolution of remote sensing products or models.

This session addresses ET estimation with both remote sensing and in-situ methods. We invite contributions that (1) assess and compare established and new in-situ and remote sensing ET estimates, (2) address uncertainty in these methods, (3) bridge spatio-temporal scales in different ET estimates (4) incorporate remote sensing and in-situ measurements into process-based modelling approaches.