Articles | Volume 20, issue 11
https://doi.org/10.5194/hess-20-4655-2016
https://doi.org/10.5194/hess-20-4655-2016
Research article
 | 
22 Nov 2016
Research article |  | 22 Nov 2016

Towards simplification of hydrologic modeling: identification of dominant processes

Steven L. Markstrom, Lauren E. Hay, and Martyn P. Clark

Related authors

Parameter regionalization of a monthly water balance model for the conterminous United States
Andrew R. Bock, Lauren E. Hay, Gregory J. McCabe, Steven L. Markstrom, and R. Dwight Atkinson
Hydrol. Earth Syst. Sci., 20, 2861–2876, https://doi.org/10.5194/hess-20-2861-2016,https://doi.org/10.5194/hess-20-2861-2016, 2016
Short summary
mizuRoute version 1: a river network routing tool for a continental domain water resources applications
Naoki Mizukami, Martyn P. Clark, Kevin Sampson, Bart Nijssen, Yixin Mao, Hilary McMillan, Roland J. Viger, Steve L. Markstrom, Lauren E. Hay, Ross Woods, Jeffrey R. Arnold, and Levi D. Brekke
Geosci. Model Dev., 9, 2223–2238, https://doi.org/10.5194/gmd-9-2223-2016,https://doi.org/10.5194/gmd-9-2223-2016, 2016
Short summary

Related subject area

Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Evaluation of hydrological models on small mountainous catchments: impact of the meteorological forcings
Guillaume Evin, Matthieu Le Lay, Catherine Fouchier, David Penot, Francois Colleoni, Alexandre Mas, Pierre-André Garambois, and Olivier Laurantin
Hydrol. Earth Syst. Sci., 28, 261–281, https://doi.org/10.5194/hess-28-261-2024,https://doi.org/10.5194/hess-28-261-2024, 2024
Short summary
Projecting sediment export from two highly glacierized alpine catchments under climate change: exploring non-parametric regression as an analysis tool
Lena Katharina Schmidt, Till Francke, Peter Martin Grosse, and Axel Bronstert
Hydrol. Earth Syst. Sci., 28, 139–161, https://doi.org/10.5194/hess-28-139-2024,https://doi.org/10.5194/hess-28-139-2024, 2024
Short summary
A framework for parameter estimation, sensitivity analysis, and uncertainty analysis for holistic hydrologic modeling using SWAT+
Salam A. Abbas, Ryan T. Bailey, Jeremy T. White, Jeffrey G. Arnold, Michael J. White, Natalja Čerkasova, and Jungang Gao
Hydrol. Earth Syst. Sci., 28, 21–48, https://doi.org/10.5194/hess-28-21-2024,https://doi.org/10.5194/hess-28-21-2024, 2024
Short summary
On understanding mountainous carbonate basins of the Mediterranean using parsimonious modeling solutions
Shima Azimi, Christian Massari, Giuseppe Formetta, Silvia Barbetta, Alberto Tazioli, Davide Fronzi, Sara Modanesi, Angelica Tarpanelli, and Riccardo Rigon
Hydrol. Earth Syst. Sci., 27, 4485–4503, https://doi.org/10.5194/hess-27-4485-2023,https://doi.org/10.5194/hess-27-4485-2023, 2023
Short summary
Comparing quantile regression forest and mixture density long short-term memory models for probabilistic post-processing of satellite precipitation-driven streamflow simulations
Yuhang Zhang, Aizhong Ye, Bita Analui, Phu Nguyen, Soroosh Sorooshian, Kuolin Hsu, and Yuxuan Wang
Hydrol. Earth Syst. Sci., 27, 4529–4550, https://doi.org/10.5194/hess-27-4529-2023,https://doi.org/10.5194/hess-27-4529-2023, 2023
Short summary

Cited articles

Ali, G., Tetzlaff, D., Soulsby, C., McDonnell, J. and Capell, R.: A comparison of similarity indices for catchment classification using a cross-regional dataset, Adv. Water Resour., 40, 11–22, https://doi.org/10.1016/j.advwatres.2012.01.008, 2012.
Amorocho, J. and Hart, W. E.: A critique of current methods in hydrologic systems investigation, Trans. Am. Geophys. Un., 45, 307–321, 1964.
Archfield, S. A., Kennen, J. G., Carlisle, D. M., and Wolock, D. M.: An objective and parsimonious approach for classifying nature flow regimes at a continental scale, River Res. Appl., 30, 1166–1183, 2014.
Battaglin, W. A., Hay, L. E., and Markstrom, S. L.: Simulating the potential effects of climate change in two Colorado Basins and at two Colorado ski areas, Earth Interact., 15, 1–23, 2011.
Beven, K: A manifesto for the equifinality thesis, J. Hydrol., 320, 18–36, https://doi.org/10.1016/j.jhydrol.2005.07.007, 2006.
Download
Short summary
Results of this study indicate that it is possible to identify the influence of different hydrologic processes when simulating with a distributed-parameter hydrology model on the basis of parameter sensitivity analysis. Identification of these processes allows the modeler to focus on the more important aspects of the model input and output, which can simplify all facets of the hydrologic modeling application.