Details zur Publikation

Kategorie Textpublikation
Referenztyp Zeitschriften
DOI 10.1175/JHM-D-15-0054.1
Titel (primär) Multiscale and multivariate evaluation of water fluxes and states over European river basins
Autor Rakovec, O. ORCID logo ; Kumar, R. ORCID logo ; Mai, J.; Cuntz, M.; Thober, S.; Zink, M.; Attinger, S.; Schäfer, D.; Schrön, M.; Samaniego, L. ORCID logo
Quelle Journal of Hydrometeorology
Erscheinungsjahr 2016
Department CHS; MET
Band/Volume 17
Heft 1
Seite von 287
Seite bis 307
Sprache englisch
UFZ Querschnittsthemen RU5;
Abstract Accurately predicting regional scale water fluxes and states remains a challenging task in contemporary hydrology. Coping with this grand challenge requires among other things a model that makes reliable predictions across scales, locations, and variables other than those used for parameter estimation. In this study, the mesoscale hydrologic model (mHM) parameterized with the multiscale regionalization technique is comprehensively tested across 400 European river basins. The model fluxes and states, constrained using the observed streamflow, are evaluated against gridded evapotranspiration data, soil moisture and total water storage anomalies, as well as local-scale eddy covariance observations. This multiscale verification is carried out in seamless manner at the native resolutions of available dataset varying from 0.5 km to 100 km. Results of cross-validation tests show that mHM is able to capture the streamflow dynamics adequately well across a wide range of climate and physiographical characteristics. The model yields generally better results (with lower spread of model statistics) in basins with higher rain gauge density. Model performance for other fluxes and states is strongly driven by the degree of seasonality that each variable exhibits with the best match being observed for evapotranspiration, followed by total water storage anomaly, and the least for soil moisture. Results show that constraining the model against streamflow only may be necessary but not sufficient to warrant the model fidelity for other complementary variables. The study emphasizes the need to account for other complementary datasets besides streamflow during parameter estimation to improve model skill with respect to “hidden” variables.
dauerhafte UFZ-Verlinkung https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=16546
Rakovec, O., Kumar, R., Mai, J., Cuntz, M., Thober, S., Zink, M., Attinger, S., Schäfer, D., Schrön, M., Samaniego, L. (2016):
Multiscale and multivariate evaluation of water fluxes and states over European river basins
J. Hydrometeorol. 17 (1), 287 - 307 10.1175/JHM-D-15-0054.1