Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 5.153
IF5.153
IF 5-year value: 5.460
IF 5-year
5.460
CiteScore value: 7.8
CiteScore
7.8
SNIP value: 1.623
SNIP1.623
IPP value: 4.91
IPP4.91
SJR value: 2.092
SJR2.092
Scimago H <br class='widget-line-break'>index value: 123
Scimago H
index
123
h5-index value: 65
h5-index65
Volume 17, issue 12
Hydrol. Earth Syst. Sci., 17, 5109–5125, 2013
https://doi.org/10.5194/hess-17-5109-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 17, 5109–5125, 2013
https://doi.org/10.5194/hess-17-5109-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 17 Dec 2013

Research article | 17 Dec 2013

From maps to movies: high-resolution time-varying sensitivity analysis for spatially distributed watershed models

J. D. Herman et al.

Related authors

Spatially distributed sensitivity of simulated global groundwater heads and flows to hydraulic conductivity, groundwater recharge, and surface water body parameterization
Robert Reinecke, Laura Foglia, Steffen Mehl, Jonathan D. Herman, Alexander Wachholz, Tim Trautmann, and Petra Döll
Hydrol. Earth Syst. Sci., 23, 4561–4582, https://doi.org/10.5194/hess-23-4561-2019,https://doi.org/10.5194/hess-23-4561-2019, 2019
Short summary
Flood and drought hydrologic monitoring: the role of model parameter uncertainty
N. W. Chaney, J. D. Herman, P. M. Reed, and E. F. Wood
Hydrol. Earth Syst. Sci., 19, 3239–3251, https://doi.org/10.5194/hess-19-3239-2015,https://doi.org/10.5194/hess-19-3239-2015, 2015
Short summary
Technical Note: Method of Morris effectively reduces the computational demands of global sensitivity analysis for distributed watershed models
J. D. Herman, J. B. Kollat, P. M. Reed, and T. Wagener
Hydrol. Earth Syst. Sci., 17, 2893–2903, https://doi.org/10.5194/hess-17-2893-2013,https://doi.org/10.5194/hess-17-2893-2013, 2013

Related subject area

Subject: Catchment hydrology | Techniques and Approaches: Uncertainty analysis
Coupled machine learning and the limits of acceptability approach applied in parameter identification for a distributed hydrological model
Aynom T. Teweldebrhan, Thomas V. Schuler, John F. Burkhart, and Morten Hjorth-Jensen
Hydrol. Earth Syst. Sci., 24, 4641–4658, https://doi.org/10.5194/hess-24-4641-2020,https://doi.org/10.5194/hess-24-4641-2020, 2020
A systematic assessment of uncertainties in large-scale soil loss estimation from different representations of USLE input factors – a case study for Kenya and Uganda
Christoph Schürz, Bano Mehdi, Jens Kiesel, Karsten Schulz, and Mathew Herrnegger
Hydrol. Earth Syst. Sci., 24, 4463–4489, https://doi.org/10.5194/hess-24-4463-2020,https://doi.org/10.5194/hess-24-4463-2020, 2020
Short summary
Technical note: Uncertainty in multi-source partitioning using large tracer data sets
Alicia Correa, Diego Ochoa-Tocachi, and Christian Birkel
Hydrol. Earth Syst. Sci., 23, 5059–5068, https://doi.org/10.5194/hess-23-5059-2019,https://doi.org/10.5194/hess-23-5059-2019, 2019
Short summary
Assessment of climate change impact and difference on the river runoff in four basins in China under 1.5 and 2.0 °C global warming
Hongmei Xu, Lüliu Liu, Yong Wang, Sheng Wang, Ying Hao, Jingjin Ma, and Tong Jiang
Hydrol. Earth Syst. Sci., 23, 4219–4231, https://doi.org/10.5194/hess-23-4219-2019,https://doi.org/10.5194/hess-23-4219-2019, 2019
Short summary
A likelihood framework for deterministic hydrological models and the importance of non-stationary autocorrelation
Lorenz Ammann, Fabrizio Fenicia, and Peter Reichert
Hydrol. Earth Syst. Sci., 23, 2147–2172, https://doi.org/10.5194/hess-23-2147-2019,https://doi.org/10.5194/hess-23-2147-2019, 2019
Short summary

Cited articles

Alton, P., Mercado, L., and North, P.: A sensitivity analysis of the land-surface scheme JULES conducted for three forest biomes: Biophysical parameters, model processes, and meteorological driving data, Global Biogeochem. Cy., 20, GB1008, https://doi.org/10.1029/2005GB002653, 2006.
Bastidas, L., Hogue, T., Sorooshian, S., Gupta, H., and Shuttleworth, W.: Parameter sensitivity analysis for different complexity land surface models using multicriteria methods, J. Geophys. Res., 111, 20101, https://doi.org/10.1029/2005JD006377, 2006.
Burnash, R. and Singh, V.: The NWS River Forecast System–Catchment Modeling, in: Computer Models of Watershed Hydrology, 311–366, Water Resour. Publ., Littleton, Colorado, 1995.
Campolongo, F., Cariboni, J., and Saltelli, A.: An effective screening design for sensitivity analysis of large models, Environ. Modell. Softw., 22, 1509–1518, 2007.
Campolongo, F., Saltelli, A., and Cariboni, J.: From screening to quantitative sensitivity analysis, A unified approach, Computer Phys. Commun., 182, 978–988, 2011.
Publications Copernicus
Download
Citation