Articles | Volume 25, issue 3
Hydrol. Earth Syst. Sci., 25, 1529–1568, 2021
https://doi.org/10.5194/hess-25-1529-2021
Hydrol. Earth Syst. Sci., 25, 1529–1568, 2021
https://doi.org/10.5194/hess-25-1529-2021

Research article 26 Mar 2021

Research article | 26 Mar 2021

Implications of model selection: a comparison of publicly available, conterminous US-extent hydrologic component estimates

Samuel Saxe et al.

Related authors

Characterization and evaluation of controls on post-fire streamflow response across western US watersheds
Samuel Saxe, Terri S. Hogue, and Lauren Hay
Hydrol. Earth Syst. Sci., 22, 1221–1237, https://doi.org/10.5194/hess-22-1221-2018,https://doi.org/10.5194/hess-22-1221-2018, 2018
Short summary

Related subject area

Subject: Global hydrology | Techniques and Approaches: Uncertainty analysis
Multi-variable evaluation of land surface processes in forced and coupled modes reveals new error sources to the simulated water cycle in the IPSL climate model
Hiroki Mizuochi, Agnes Ducharne, Frédérique Cheruy, Josefine Ghattas, Amen Al-Yaari, Jean-Pierre Wigneron, Philippe Peylin, Fabienne Maignan, and Nicolas Vuichard
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-438,https://doi.org/10.5194/hess-2020-438, 2020
Revised manuscript accepted for HESS
Historical and future changes in global flood magnitude – evidence from a model–observation investigation
Hong Xuan Do, Fang Zhao, Seth Westra, Michael Leonard, Lukas Gudmundsson, Julien Eric Stanislas Boulange, Jinfeng Chang, Philippe Ciais, Dieter Gerten, Simon N. Gosling, Hannes Müller Schmied, Tobias Stacke, Camelia-Eliza Telteu, and Yoshihide Wada
Hydrol. Earth Syst. Sci., 24, 1543–1564, https://doi.org/10.5194/hess-24-1543-2020,https://doi.org/10.5194/hess-24-1543-2020, 2020
Short summary
A global-scale evaluation of extreme event uncertainty in the eartH2Observe project
Toby R. Marthews, Eleanor M. Blyth, Alberto Martínez-de la Torre, and Ted I. E. Veldkamp
Hydrol. Earth Syst. Sci., 24, 75–92, https://doi.org/10.5194/hess-24-75-2020,https://doi.org/10.5194/hess-24-75-2020, 2020
Short summary
Assessment of precipitation error propagation in multi-model global water resource reanalysis
Md Abul Ehsan Bhuiyan, Efthymios I. Nikolopoulos, Emmanouil N. Anagnostou, Jan Polcher, Clément Albergel, Emanuel Dutra, Gabriel Fink, Alberto Martínez-de la Torre, and Simon Munier
Hydrol. Earth Syst. Sci., 23, 1973–1994, https://doi.org/10.5194/hess-23-1973-2019,https://doi.org/10.5194/hess-23-1973-2019, 2019
Short summary
The potential of global reanalysis datasets in identifying flood events in Southern Africa
Gaby J. Gründemann, Micha Werner, and Ted I. E. Veldkamp
Hydrol. Earth Syst. Sci., 22, 4667–4683, https://doi.org/10.5194/hess-22-4667-2018,https://doi.org/10.5194/hess-22-4667-2018, 2018
Short summary

Cited articles

Abatzoglou, J. T.: Development of gridded surface meteorological data for ecological applications and modelling, Int. J. Climatol., 33, 121–131, https://doi.org/10.1002/joc.3413, 2013. 
Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A., and Hegewisch, K. C.: TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015, Scientific Data, 5, 170191, 2018. 
Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21, 5293–5313, https://doi.org/10.5194/hess-21-5293-2017, 2017. 
Al Bitar, A., Kerr, Y. H., Merlin, O., Cabot, F., and Wigneron, J.-P.: Global drought index from SMOS soil moisture, Geoscience and Remote Sensing Symposium (IGARSS), 21 February 2013, Melbourne, Australia, 2013. 
Alsdorf, D. E., Rodrigues, E., and Lettenmaier, D. P.: Measuring surface water from space, Rev. Geophys., 45, 2, https://doi.org/10.1029/2006RG000197, 2007. 
Download
Short summary
We compare simulated values from 47 models estimating surface water over the USA. Results show that model uncertainty is substantial over much of the conterminous USA and especially high in the west. Applying the studied models to a simple water accounting equation shows that model selection can significantly affect research results. This paper concludes that multimodel ensembles help to best represent uncertainty in conclusions and suggest targeted research efforts in arid regions.