Abstract. So far, various studies have aimed at decomposing the
integrated terrestrial water storage variations observed by satellite
gravimetry (GRACE, GRACE-FO) with the help of large-scale hydrological
models. While the results of the storage decomposition depend on model
structure, little attention has been given to the impact of the way that
vegetation is represented in these models. Although vegetation structure and
activity represent the crucial link between water, carbon, and energy cycles,
their representation in large-scale hydrological models remains a major
source of uncertainty. At the same time, the increasing availability and
quality of Earth-observation-based vegetation data provide valuable
information with good prospects for improving model simulations and gaining
better insights into the role of vegetation within the global water cycle. In this study, we use observation-based vegetation information such as
vegetation indices and rooting depths for spatializing the parameters of a
simple global hydrological model to define infiltration, root water uptake,
and transpiration processes. The parameters are further constrained by
considering observations of terrestrial water storage anomalies (TWS), soil
moisture, evapotranspiration (ET) and gridded runoff (Q) estimates in a
multi-criteria calibration approach. We assess the implications of including
varying vegetation characteristics on the simulation results, with a
particular focus on the partitioning between water storage components. To
isolate the effect of vegetation, we compare a model experiment in which
vegetation parameters vary in space and time to a baseline experiment in
which all parameters are calibrated as static, globally uniform values. Both experiments show good overall performance, but explicitly including
varying vegetation data leads to even better performance and more physically
plausible parameter values. The largest improvements regarding TWS and ET are
seen in supply-limited (semi-arid) regions and in the tropics, whereas Q
simulations improve mainly in northern latitudes. While the total fluxes and
storages are similar, accounting for vegetation substantially changes the
contributions of different soil water storage components to the TWS
variations. This suggests an important role of the representation of
vegetation in hydrological models for interpreting TWS variations. Our
simulations further indicate a major effect of deeper moisture storages and
groundwater–soil moisture–vegetation interactions as a key to understanding
TWS variations. We highlight the need for further observations to identify
the adequate model structure rather than only model parameters for a
reasonable representation and interpretation of vegetation–water
interactions.
