Articles | Volume 19, issue 9
Hydrol. Earth Syst. Sci., 19, 3891–3901, 2015
Hydrol. Earth Syst. Sci., 19, 3891–3901, 2015

Research article 16 Sep 2015

Research article | 16 Sep 2015

Climate model uncertainty versus conceptual geological uncertainty in hydrological modeling

T. O. Sonnenborg et al.

Related authors

Are maps of nitrate reduction in groundwater altered by climate and land use changes?
Ida Karlsson Seidenfaden, Torben Obel Sonnenborg, Jens Christian Refsgaard, Christen Duus Børgesen, Jørgen Eivind Olesen, and Dennis Trolle
Hydrol. Earth Syst. Sci. Discuss.,,, 2020
Revised manuscript accepted for HESS
Short summary
Modelling of the shallow water table at high spatial resolution using random forests
Julian Koch, Helen Berger, Hans Jørgen Henriksen, and Torben Obel Sonnenborg
Hydrol. Earth Syst. Sci., 23, 4603–4619,,, 2019
Short summary
Estimation of effective porosity in large-scale groundwater models by combining particle tracking, auto-calibration and 14C dating
Rena Meyer, Peter Engesgaard, Klaus Hinsby, Jan A. Piotrowski, and Torben O. Sonnenborg
Hydrol. Earth Syst. Sci., 22, 4843–4865,,, 2018
The effect of training image and secondary data integration with multiple-point geostatistics in groundwater modelling
X. L. He, T. O. Sonnenborg, F. Jørgensen, and K. H. Jensen
Hydrol. Earth Syst. Sci., 18, 2943–2954,,, 2014
Historical trends in precipitation and stream discharge at the Skjern River catchment, Denmark
I. B. Karlsson, T. O. Sonnenborg, K. H. Jensen, and J. C. Refsgaard
Hydrol. Earth Syst. Sci., 18, 595–610,,, 2014

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., 25, 4995–5011,,, 2021
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,,, 2020
Short summary
Quantifying input uncertainty in the calibration of water quality models: reshuffling errors via the secant method
Xia Wu, Lucy Marshall, and Ashish Sharma
Hydrol. Earth Syst. Sci. Discuss.,,, 2020
Revised manuscript accepted for HESS
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,,, 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,,, 2020
Short summary

Cited articles

Bastola, S., Murphy, C., and Sweeny, J.: The role of hydrological modelling uncertainties in climate change impact assessments of Irish river catchments, Adv. Water Resour., 34, 562–576, 2011.
Bredehoeft J.: The conceptualization model problem – Surprise, Hydrogeol. J., 13, 37–46, 2005.
Christensen, J. H., Rummukainen, M., and Lenderink, G.: Formulation of very-high-resolution regional climate model ensembles for Europe [Research Theme 3], ENSEMBLES: Climate Change and its Impacts: Summary of research and results from the ENSEMBLES project, Met Office Hadley Centre, UK, 47–58, 2009.
Déqué, M., Rowell, D. P., Lüthi, D., Giorgi, F., Christensen, J.H., Rockel, B., Jacob, D., Kjellström, E., de Castro, M., and van den Hurk, B.: An Intercomparison of Regional Climate Model Simulations for Europe: Assessing Uncertainties in Model Predictions, Clim. Change, 81, 53–70, 2007.
DHI Water and Environment (DHI): MIKE SHE User manual, vol. 1; user guide, and vol. 2: reference guide, Institut for Vand andMilljo, available at: (last access: 1 February 2013), DHI, Hørsholm, Denmark, 2009a.
Short summary
The impacts of climate model uncertainty and geological model uncertainty on hydraulic head, stream flow, travel time and capture zones are evaluated. Six versions of a physically based and distributed hydrological model, each containing a unique interpretation of the geological structure of the model area, are forced by 11 climate model projections. Geology is the dominating uncertainty source for travel time and capture zones, while climate dominates for hydraulic heads and steam flow.