Abstract
Streamflow is often the only variable used to evaluate hydrological models. In a previous international comparison study, eight research groups followed an identical protocol to calibrate 12 hydrological models using observed streamflow of catchments within the Meuse basin. In the current study, we quantify the differences in five states and fluxes of these 12 process-based models with similar streamflow performance, in a systematic and comprehensive way. Next, we assess model behavior plausibility by ranking the models for a set of criteria using streamflow and remote-sensing data of evaporation, snow cover, soil moisture and total storage anomalies. We found substantial dissimilarities between models for annual interception and seasonal evaporation rates, the annual number of days with water stored as snow, the mean annual maximum snow storage and the size of the root-zone storage capacity. These differences in internal process representation imply that these models cannot all simultaneously be close to reality. Modeled annual evaporation rates are consistent with Global Land Evaporation Amsterdam Model (GLEAM) estimates. However, there is a large uncertainty in modeled and remote-sensing annual interception. Substantial differences are also found between Moderate Resolution Imaging Spectroradiometer (MODIS) and modeled number of days with snow storage. Models with relatively small root-zone storage capacities and without root water uptake reduction under dry conditions tend to have an empty root-zone storage for several days each summer, while this is not suggested by remote-sensing data of evaporation, soil moisture and vegetation indices. On the other hand, models with relatively large root-zone storage capacities tend to overestimate very dry total storage anomalies of the Gravity Recovery and Climate Experiment (GRACE). None of the models is systematically consistent with the information available from all different (remote-sensing) data sources. Yet we did not reject models given the uncertainties in these data sources and their changing relevance for the system under investigation.
| Original language | English |
|---|---|
| Article number | 56 |
| Pages (from-to) | 1069-1095 |
| Number of pages | 27 |
| Journal | Hydrology and Earth System Sciences |
| Volume | 25 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2 Mar 2021 |
Bibliographical note
Funding Information:Data availability. Streamflow and precipitation data were provided by the Service Public de Wallonie in Belgium (Direction générale opérationnelle de la Mobilité et des Voies hydrauliques, Départe-ment des Etudes et de l’Appui à la Gestion, Direction de la Gestion hydrologique intégrée (Bld du Nord 8-5000 Namur, Belgium)). Hourly radiation data were retrieved from the portal of the Royal Netherlands Meteorological Institute (http://www.knmi. nl/nederland-nu/klimatologie/uurgegevens, Royal Netherlands Meteorological Institute, 2018). Daily temperature data were retrieved from the E-OBS (version 17.0) OPeNDAP server (Haylock et al., 2008; Cornes et al., 2018). Actual evaporation estimates from the Global Land Evaporation Amsterdam Model (GLEAM) are available through the SFTP server of GLEAM (https://www.gleam. eu/, Global Land Evaporation Amsterdam Model, 2021; Miralles et al., 2011; Martens et al., 2017). MODIS snow cover fractions are available for download from the Earthdata portal at https://doi.org/10.5067/MODIS/MOD10A1.006 (Hall and Riggs, 2016a) and https://doi.org/10.5067/MODIS/MYD10A1.006 (Hall and Riggs, 2016b). MODIS vegetation indices data are available for download at https://doi.org/10.5067/MODIS/MOD13A1.006 (Didan, 2015a) and https://doi.org/10.5067/MODIS/MYD13A1.006 (Didan, 2015b). The Soil Water Index SCATSAR-SWI1km is available from the Copernicus Global Land Service at https:// land.copernicus.eu/global/products/swi (Copernicus Global Land Service, 2019; Bauer-Marschallinger et al., 2018). GRACE land data (Swenson and Wahr, 2006; Landerer and Swen-son, 2012; Swenson, 2012) are available at http://grace.jpl.nasa. gov (NASA’s MEaSUREs Program, 2021), supported by the NASA MEaSUREs program. The modeled states and fluxes of each model are available online in the 4TU data repository at https://doi.org/10.4121/13221038.v1 (Bouaziz et al., 2021).
Funding Information:
Acknowledgements. We thank Deltares and Rijkswaterstaat for the financial support to conduct this analysis. The authors would like to thank the Service Public de Wallonie, Direction générale opéra-tionnelle de la Mobilité et des Voies hydrauliques, Département des Etudes et de l’Appui à la Gestion, Direction de la Gestion hy-drologique intégrée (Bld du Nord 8-5000 Namur, Belgium) for providing the precipitation and streamflow data. We are grateful for the E-OBS dataset from EU-FP6 project UERRA (http://www.uerra.eu, last access: 21 February 2021) and the Copernicus Climate Change Service and the data providers in the ECA&D project (https://www. ecad.eu, last access: 21 February 2021). We thank the editor Nadav Peleg, Keith Beven, Shervan Gharari, Uwe Ehret and three anonymous referees for their constructive comments which helped us improve the manuscript.
Funding Information:
We thank Deltares and Rijkswaterstaat for the financial support to conduct this analysis. The authors would like to thank the Service Public de Wallonie, Direction g?n?rale op?rationnelle de la Mobilit? et des Voies hydrauliques, D?partement des Etudes et de l'Appui ? la Gestion, Direction de la Gestion hydrologique int?gr?e (Bld du Nord 8-5000 Namur, Belgium) for providing the precipitation and streamflow data. We are grateful for the E-OBS dataset from EU-FP6 project UERRA (http://www.uerra.eu, last access: 21 February 2021) and the Copernicus Climate Change Service and the data providers in the ECA&D project (https://www. ecad.eu, last access: 21 February 2021). We thank the editor Nadav Peleg, Keith Beven, Shervan Gharari, Uwe Ehret and three anonymous referees for their constructive comments which helped us improve the manuscript.
Publisher Copyright:
© Author(s) 2021.