Spatially distributed sensitivity of simulated global groundwater heads and flows to hydraulic conductivity; groundwater recharge; and surface water body parameterization
Distributed parameter control systems
; Domain decomposition methods
; Hydraulic conductivity
; Reservoirs (water)
; Spatial distribution
; Surface waters
; Uncertainty analysis
; Calibration parameters
; Ground water-surface water interactions
; Hydrological response unit
; Numerical instability
; Parameter combination
; Parameter sensitivities
; Spatially distributed parameters
; Steady-state modeling
; Recharging (underground waters)
; groundwater-surface water interaction
; hydraulic conductivity
; hydraulic head
; hydrological modeling
; hydrological response
; parameterization
; recharge
; simulation
; spatial distribution
英文摘要:
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 and by uncertain model assumptions that are necessary due to the coarse spatial resolution. The impact of data quality is presented in this study by showing the sensitivity of a groundwater model to changes in the only available global hydraulic conductivity dataset. To better understand the sensitivity of model output to uncertain spatially distributed parameters, 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 in simulating the direction of flow between the two compartments. Mountainous and dry regions show a high variance in simulated head due to numerical instabilities of the model, limiting the reliability of computed sensitivities in these regions. This is likely caused by the uncertainty in surface water body elevation. We conclude that maps of spatially distributed sensitivities can help to understand the complex behavior 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.
Reinecke, R., Institute of Physical Geography, Goethe University Frankfurt, Frankfurt am Main, Germany; Foglia, L., Department of Land, Air and Water Resources, University of California, Davis, CA, United States; Mehl, S., Department of Civil Engineering, California State University, Chico, CA, United States; Herman, J.D., Department of Civil and Environmental Engineering, University of California, Davis, CA, United States; Wachholz, A., Institute of Physical Geography, Goethe University Frankfurt, Frankfurt am Main, Germany; Trautmann, T., Institute of Physical Geography, Goethe University Frankfurt, Frankfurt am Main, Germany; Döll, P., Institute of Physical Geography, Goethe University Frankfurt, Frankfurt am Main, Germany, Senckenberg Leibniz Biodiversity and Climate Research Centre Frankfurt (SBiK-F), Frankfurt am Main, Germany
Recommended Citation:
Reinecke R.,Foglia L.,Mehl S.,et al. Spatially distributed sensitivity of simulated global groundwater heads and flows to hydraulic conductivity; groundwater recharge; and surface water body parameterization[J]. Hydrology and Earth System Sciences,2019-01-01,23(11)