Articles | Volume 20, issue 2
Hydrol. Earth Syst. Sci., 20, 887–901, 2016
https://doi.org/10.5194/hess-20-887-2016
Hydrol. Earth Syst. Sci., 20, 887–901, 2016
https://doi.org/10.5194/hess-20-887-2016

Research article 26 Feb 2016

Research article | 26 Feb 2016

Accounting for dependencies in regionalized signatures for predictions in ungauged catchments

Susana Almeida et al.

Related authors

Epistemic uncertainties and natural hazard risk assessment – Part 1: A review of different natural hazard areas
Keith J. Beven, Susana Almeida, Willy P. Aspinall, Paul D. Bates, Sarka Blazkova, Edoardo Borgomeo, Jim Freer, Katsuichiro Goda, Jim W. Hall, Jeremy C. Phillips, Michael Simpson, Paul J. Smith, David B. Stephenson, Thorsten Wagener, Matt Watson, and Kate L. Wilkins
Nat. Hazards Earth Syst. Sci., 18, 2741–2768, https://doi.org/10.5194/nhess-18-2741-2018,https://doi.org/10.5194/nhess-18-2741-2018, 2018
Short summary
Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change
Susana Almeida, Elizabeth Ann Holcombe, Francesca Pianosi, and Thorsten Wagener
Nat. Hazards Earth Syst. Sci., 17, 225–241, https://doi.org/10.5194/nhess-17-225-2017,https://doi.org/10.5194/nhess-17-225-2017, 2017
Short summary
Epistemic uncertainties and natural hazard risk assessment – Part 2: Different natural hazard areas
K. J. Beven, S. Almeida, W. P. Aspinall, P. D. Bates, S. Blazkova, E. Borgomeo, K. Goda, J. C. Phillips, M. Simpson, P. J. Smith, D. B. Stephenson, T. Wagener, M. Watson, and K. L. Wilkins
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2015-295,https://doi.org/10.5194/nhess-2015-295, 2016
Preprint withdrawn
Short summary

Related subject area

Subject: Catchment hydrology | Techniques and Approaches: Uncertainty analysis
Sequential Data Assimilation for Real-Time Probabilistic Flood Inundation Mapping
Keighobad Jafarzadegan, Peyman Abbaszadeh, and Hamid Moradkhani
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-181,https://doi.org/10.5194/hess-2021-181, 2021
Revised manuscript accepted for HESS
Short summary
Key challenges facing the application of the conductivity mass balance method: a case study of the Mississippi River basin
Hang Lyu, Chenxi Xia, Jinghan Zhang, and Bo Li
Hydrol. Earth Syst. Sci., 24, 6075–6090, https://doi.org/10.5194/hess-24-6075-2020,https://doi.org/10.5194/hess-24-6075-2020, 2020
Short summary
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

Cited articles

Almeida, S. M. C. L.: The Value of Regionalised Information for Hydrological Modelling, PhD thesis, Imperial College London, London, UK, 2014.
Almeida, S., Bulygina, N., McIntyre, N., Wagener, T., and Buytaert, W.: Predicting flows in ungauged catchments using correlated information sources, in: British Hydrological Society's Eleventh National Hydrology Symposium, Hydrology for a Changing World, Dundee, UK, 2012.
Almeida, S., Bulygina, N., McIntyre, N., Wagener, T., and Buytaert, W.: Improving parameter priors for data-scarce estimation problems, Water Resour. Res., 49, 6090–6095, https://doi.org/10.1002/wrcr.20437, 2013.
Arnold, J. G. and Allen, P. M.: Automated methods for estimating baseflow and ground water recharge from streamflow records, J. Am. Water Resour. As., 35, 411–424, https://doi.org/10.1111/j.1752-1688.1999.tb03599.x, 1999.
Boorman, D. B., Hollis, J. M., and Lilly, A.: Hydrology of soil types: a hydrologically-based classification of the soils of the United Kingdom, Tech. rep., Institute of Hydrology, Wallingford, UK, 1995.
Download
Short summary
The absence of flow data to calibrate hydrologic models may reduce the ability of such models to reliably inform water resources management. To address this limitation, it is common to condition hydrological model parameters on regionalized signatures. In this study, we justify the inclusion of larger sets of signatures in the regionalization procedure if their error correlations are formally accounted for and thus enable a more complete use of all available information.