Spatially distributed sensitivity of simulated global groundwater heads and flows to hydraulic conductivity, groundwater recharge and surface water body parameterization

  • In global hydrological models, groundwater storages and flows are generally simulated by linear reservoir models. Recently, the first global gradient-based groundwater models were developed in order to improve the representation of groundwater-surface water interactions, capillary rise, lateral flows and human water use impacts. However, the reliability of model outputs is limited by a lack of data as well as model assumptions required due to the necessarily coarse spatial resolution. The impact of data quality is presented by showing the sensitivity of a groundwater model to changes in the only available global hydraulic conductivity data-set. To better understand the sensitivity of model output to uncertain spatially distributed parameter inputs, we present the first application of a global sensitivity method for a global-scale groundwater model using nearly 2000 steady-state model runs of the global gradient-based groundwater model G3M. By applying the Morris method in a novel domain decomposition approach that identifies global hydrological response units, spatially distributed parameter sensitivities are determined for a computationally expensive model. Results indicate that globally simulated hydraulic heads are equally sensitive to hydraulic conductivity, groundwater recharge and surface water body elevation, though parameter sensitivities vary regionally. For large areas of the globe, rivers are simulated to be either losing or gaining, depending on the parameter combination, indicating a high uncertainty of simulating the direction of flow between the two compartments. Mountainous and dry regions show a high variance in simulated head due to numerical difficulties of the model, limiting the reliability of computed sensitivities in these regions. This instability is likely caused by the uncertainty in surface water body elevation. We conclude that maps of spatially distributed sensitivities can help to understand complex behaviour of models that incorporate data with varying spatial uncertainties. The findings support the selection of possible calibration parameters and help to anticipate challenges for a transient coupling of the model.

Download full text files

Export metadata

Author:Robert ReineckeORCiDGND, Laura Foglia, Steffen Mehl, Jonathan D. Herman, Alexander Wachholz, Tim TrautmannORCiD, Petra DöllORCiDGND
Parent Title (English):Hydrology and earth system sciences discussions
Place of publication:Katlenburg-Lindau
Document Type:Article
Year of Completion:2019
Date of first Publication:2019/02/18
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2019/04/11
Page Number:26
First Page:1
Last Page:26
© Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License.
Institutes:Geowissenschaften / Geographie / Geowissenschaften
Angeschlossene und kooperierende Institutionen / Senckenbergische Naturforschende Gesellschaft
Fachübergreifende Einrichtungen / Biodiversität und Klima Forschungszentrum (BiK-F)
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Licence (German):License LogoCreative Commons - Namensnennung 4.0