Articles | Volume 19, issue 7
https://doi.org/10.5194/hess-19-3239-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-19-3239-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Flood and drought hydrologic monitoring: the role of model parameter uncertainty
N. W. Chaney
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA
J. D. Herman
School of Civil and Environmental Engineering, Cornell University, Ithaca, NY, USA
P. M. Reed
School of Civil and Environmental Engineering, Cornell University, Ithaca, NY, USA
E. F. Wood
Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA
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- Comparison of single-site, multi-site and multi-variable SWAT calibration strategies A. Franco et al. 10.1080/02626667.2020.1810252
- Parameter uncertainty and temporal dynamics of sensitivity for hydrologic models: A hybrid sequential data assimilation and probabilistic collocation method Y. Fan et al. 10.1016/j.envsoft.2016.09.012
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- Towards simplification of hydrologic modeling: identification of dominant processes S. Markstrom et al. 10.5194/hess-20-4655-2016
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- Toward improving drought monitoring using the remotely sensed soil moisture assimilation: A parallel particle filtering framework H. Yan et al. 10.1016/j.rse.2018.07.017
- Observational Uncertainty for Global Drought‐Pluvial Volatility Y. Li et al. 10.1029/2022WR034263
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- Effects of uncertainty in soil properties on simulated hydrological states and fluxes at different spatio-temporal scales G. Baroni et al. 10.5194/hess-21-2301-2017
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Short summary
Land surface modeling is playing an increasing role in global monitoring and prediction of extreme hydrologic events. However, uncertainties in parameter identifiability limit the reliability of model predictions. This study makes use of petascale computing to perform a comprehensive evaluation of land surface modeling for global flood and drought monitoring and suggests paths forward to overcome the challenges posed by parameter uncertainty.
Land surface modeling is playing an increasing role in global monitoring and prediction of...