Measuring Evapotranspiration at the Cabauw Experimental Site for Atmospheric Research

Droughts in the Netherlands have been exacerbated by climate change, urging better scientific understanding of the hydrological cycle and the role of evapotranspiration. Evapotranspiration is the combined process in which liquid water is transferred from the surface to the atmosphere as water vapor, occurring through evaporation as well as transpiration from vegetation leaves. In addition to better understanding how water leaves the Earth’s surface, accurate surface water observations are crucial for reliable predictions and effective management. Currently, the Royal Netherlands Meteorological Institute (KNMI) primarily estimates evaporation based on the meteorological conditions, such as precipitation and temperature. Also, their Cabauw Experimental Site for Atmospheric Research has maintained decades of in-situ evaporation observations, exploring various indirect methods, such as the eddy covariance and Bowen ratio method. Specifically, the moisture fluxes derived from turbulence and psychrometer measurements are used to determine latent energy. Although these established methods provide valuable climate insight, more direct approaches are required to improve our understanding of surface moisture loss. To address this, a new smart lysimeter has been deployed since 2020, measuring water inflow and outflow of a representative soil-vegetation column. While lysimeters offer precise measurements, they are spatially limited, sensitive to small-scale variations, and require rigorous validation. Therefore, in addition to providing an overview of the increasing evaporation observed at the Cabauw site, this study evaluates the lysimeter’s performance and potential as a reference through intercomparison. Additionally, by integrating supplementary in-situ measurements, our findings suggest that validated lysimeter data can contribute to improved closure of the surface energy balance. In this way, lysimeter observations can enhance hydrological research, improve modeling, and support environmental decision-making.