Articles | Volume 23, issue 11
https://doi.org/10.5194/hess-23-4561-2019
https://doi.org/10.5194/hess-23-4561-2019
Research article
 | 
14 Nov 2019
Research article |  | 14 Nov 2019

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

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Cited articles

Allen, P. M., Arnold, J. C., and Byars, B. W.: Downstream channel geometry for use in planning-level models, J. Am. Water Resour. Assoc., 30, 663–671, https://doi.org/10.1111/j.1752-1688.1994.tb03321.x, 1994. a
Archer, G., Saltelli, A., and Sobol, I.: Sensitivity measures, ANOVA-like techniques and the use of bootstrap, J. Stat. Comput. Simul., 58, 99–120, 1997. a, b
Börker, J., Hartmann, J., Amann, T., and Romero-Mujalli, G.: Global Unconsolidated Sediments Map Database v1.0 (shapefile and gridded to 0.5 spatial resolution), https://doi.org/10.1594/PANGAEA.884822, supplement to: Börker, J., et al. (accepted): Terrestrial Sediments of the Earth: Development of a Global Unconsolidated Sediments Map Database (GUM), Geochem. Geophy. Geosy., https://doi.org/10.1002/2017GC007273, 2018. a, b, c
Branger, F., Giraudet, L.-G., Guivarch, C., and Quirion, P.: Global sensitivity analysis of an energy–economy model of the residential building sector, Environ. Model. Softw., 70, 45–54, https://doi.org/10.1016/j.envsoft.2015.03.021, 2015. a
Campolongo, F., Cariboni, J., and Saltelli, A.: An effective screening design for sensitivity analysis of large models, Environ. Model. Softw., 22, 1509–1518, https://doi.org/10.1016/j.envsoft.2006.10.004, 2007. a, b, c, d, e
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Short summary
Recently, the first global groundwater models were developed to better understand surface-water–groundwater interactions 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. In this study we present the first global maps of model sensitivity according to their parameterization and build a foundation to improve datasets, model design, and model understanding.