03 Aug 2021

03 Aug 2021

Review status: this preprint is currently under review for the journal HESS.

The importance of vegetation to understand terrestrial water storage variations

Tina Trautmann1,2, Sujan Koirala1, Nuno Carvalhais1,3, Andreas Güntner4,5, and Martin Jung1 Tina Trautmann et al.
  • 1Max-Planck Institute for Biogeochemistry, Jena, 07745, Germany
  • 2International Max Planck Research School for Global Biogeochemical Cycles, Jena, 07745, Germany
  • 3Universidade Nova de Lisboa, Caparica, 2829-516, Portugal
  • 4German Research Centre for Geoscience, Potsdam, 14473, Germany
  • 5University of Potsdam, Potsdam, 14476, Germany

Abstract. So far, various studies 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 how 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 vegetation 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 with vegetation parameters varying 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 including vegetation data led to even better performance and more physically plausible parameter values. Largest improvements regarding TWS and ET were 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 snow and different soil water storage components to the TWS variations, with the dominance of an intermediate water pool that interacts with the fast plant accessible soil moisture and the delayed water storage. The findings indicate the important role of deeper moisture storages as well as 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.

Tina Trautmann et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-394', Anonymous Referee #1, 25 Aug 2021
  • RC2: 'Comment on hess-2021-394', Anonymous Referee #2, 28 Aug 2021
  • RC3: 'Comment on hess-2021-394', Anonymous Referee #3, 09 Sep 2021

Tina Trautmann et al.

Tina Trautmann et al.


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Short summary
We assess the effect of how vegetation is defined in a global hydrological model on the composition of total water storage (TWS). We compare 2 experiments, one with globally uniform and one with vegetation parameter that vary in space and time. While both experiments are constrained against observational data, we found a drastic change in the partitioning of TWS, highlighting an important role of the interaction between groundwater-soil moisture-vegetation to understand TWS variations.