Assessing the effects of spatial discretization on large-scale flow model performance and prediction uncertainty

Wildemeersch, Samuel; Goderniaux, Pascal; Orban, Philippe; Brouyère, Serge; Dassargues, Alain

doi:10.1016/j.jhydrol.2013.12.020

Download

Article (Scientific journals)

Assessing the effects of spatial discretization on large-scale flow model performance and prediction uncertainty

Wildemeersch, Samuel; Goderniaux, Pascal; Orban, Philippe et al.

2014 • In Journal of Hydrology, 510, p. 10-25

Peer Reviewed verified by ORBi

Permalink
https://hdl.handle.net/2268/160642

DOI
10.1016/j.jhydrol.2013.12.020

Files (1)Send to Details Statistics Bibliography Similar publications

Files

Full Text

HYDROL15539R1_2.pdf

Author preprint (1.16 MB)

The final paper can be found directly on Science Direct : http://www.sciencedirect.com/science/article/pii/S0022169413009177

Download

The final paper can be found directly on Science Direct : http://www.sciencedirect.com/science/article/pii/S0022169413009177

All documents in ORBi are protected by a user license.

Send to

RIS BibTex APA Chicago Permalink X Linkedin

Details

Keywords :

spatial discretization; model performance; sensitivity analysis; automatic calibration; prediction uncertainty

Abstract :

[en] Large-scale physically-based and spatially-distributed models (>100 km2) constitute useful tools for water management since they take explicitly into account the heterogeneity and the physical processes occurring in the subsurface for predicting the evolution of discharge and hydraulic heads for several predictive scenarios. However, such models are characterized by lengthy execution times. Therefore, modelers often coarsen spatial discretization of large-scale physically-based and spatially-distributed models for reducing the number of unknowns and the execution times. This study investigates the influence of such a coarsening of model grid on model performance and prediction uncertainty. The improvement of model performance obtained with an automatic calibration process is also investigated. The results obtained show that coarsening spatial discretization mainly influences the simulation of discharge due to a poor representation of surface water network and a smoothing of surface slopes that prevents from simulating properly surface water-groundwater interactions and runoff processes. Parameter sensitivities are not significantly influenced by grid coarsening and calibration can compensate, to some extent, for model errors induced by grid coarsening. The results also show that coarsening spatial discretization mainly influences the uncertainty on discharge predictions. However, model prediction uncertainties on discharge only increase significantly for very coarse spatial discretizations.

Disciplines :

Geological, petroleum & mining engineering

Author, co-author :

Wildemeersch, Samuel ; Université de Liège - ULiège > Département ArGEnCo > Hydrogéologie & Géologie de l'environnement

Goderniaux, Pascal; Université de Mons-Hainaut - UMH > Faculté Polytechnique > Géologie Fondamentale et Appliquée

Orban, Philippe ; Université de Liège - ULiège > Département ArGEnCo > Hydrogéologie & Géologie de l'environnement

Brouyère, Serge ; Université de Liège - ULiège > Département ArGEnCo > Hydrogéologie & Géologie de l'environnement

Dassargues, Alain ; Université de Liège - ULiège > Département ArGEnCo > Hydrogéologie & Géologie de l'environnement

Language :

English

Title :

Assessing the effects of spatial discretization on large-scale flow model performance and prediction uncertainty

Publication date :

2014

Journal title :

Journal of Hydrology

ISSN :

0022-1694

eISSN :

1879-2707

Publisher :

Elsevier Science

Volume :

510

Pages :

10-25

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

http://www.sciencedirect.com/science/article/pii/S0022169413009177

Available on ORBi :

since 06 January 2014

Statistics

Number of views

165 (25 by ULiège)

Number of downloads

465 (14 by ULiège)

More statistics

Scopus citations^®

Scopus citations^®
without self-citations

OpenCitations

OpenAlex citations

Bibliography

Anderman E., Hill M.C., Poeter E.P. Two-dimensional advective transport in ground-water flow parameter estimation. Ground Water 1996, 34(6):1001-1009.
Andersen J., Dybkjaer G., Jensen K., Refsgaard J.C., Rasmussen K. Use of remotely sensed precipitation and leaf area index in a distributed hydrological model. Journal of Hydrology 2002, 264(1-4):34-50.
Aricò C., Nasello C., Tucciarelli T. Using steady-state water level data to estimate channel roughness and discharge hydrograph. Adv. Water Resour. 2009, 32(8):1223-1240.
Asner G., Scurlock J., Hicke J. Global synthesis of leaf area index observations: implications for ecological and remote sensing studies. Global Ecology and Biogeography 2003, 12(3):191-205.
Bauer S., Beyer C., Kolditz O. Assessing measurement uncertainty of first-order degradation rates in heterogeneous aquifers. Water Resour. Res. 2006, 42(W01420).
Beyer C., Bauer S., Kolditz O. Uncertainty assessment of contaminant plume length estimates in heterogeneous aquifers. J. Contam. Hydrol. 2006, 87(1-2):73-95.
Brouyère S., Gesels J., Goderniaux P., Robert T., Thomas L., Dassargues A., Bastien J., Van Wittenberge F., Rorive A., Dossin F., Lacour J.-L., Le Madec D., Nogarède P., Hallet V., Caractérisation hydrogéologique et support à la mise en œuvre de la Directive Européenne 2000/60 sur les masses d'eau souterraine en Région Wallonne (Projet Synclin'EAU), Délivrable D.2.22 - partie MESO RWM021, 2009, Convention RW et SPGE-AquapÔle.
Brunner P., Doherty J., Simmons C.T. Uncertainty assessment and implications for data acquisition in support of integrated hydrologic models. Water Resour. Res. 2012, 48(W07513).
Brunner P., Simmons C.T. HydroGeoSphere: A fully-integrated, physically-based hydrological model. Ground Water 2012, 50(2):170-176.
Brutsaert W. Hydrology: an introduction, Cambridge 2005, Cambridge University Press, United Kingdom.
Canadell J., Jackson R., Ehleringer J., Mooney H., Sala O., Schulze E.-D. Maximum rooting depth of vegetation types at the global scale. Oecologia 1996, 108(4):583-595.
Dickinson R., Henderson-Sellers A., Rosenzweig C., Sellers P. Evapotranspiration models with canopy resistance for use in climate models, a review. Agricultural and Forest Meteorology 1991, 54(2-4):373-388.
Doherty, J., 2005. PEST - Model-Independent Parameter Estimation - User Manual, fifth ed., Watermark Numerical Computing.
Dohery J., Christensen S. Use of paired simple and complex models to reduce predictive bias and quantify uncertainty. Water Resour. Res. 2011, 47(W12534).
Downer C.W., Ogden F.L. Appropriate vertical discretization of Richards' equation for two-dimensional watershed-scale modelling. Hydrol. Process. 2004, 18:1-22.
Ebel B., Loague K. Physics-based hydrologic-response simulation: seeing through the fog of equifinality. Hydrol. Process. 2006, 20(13):2887-2900.
Fetter C., Hydrogeology Applied Upper Saddle River 2001, Prentice Hall, NJ, USA.
Freeze R., Cherry J. Groundwater, Upper Saddle River 1979, Prentice Hall, NJ, USA.
Frei S., Fleckenstein J.H., Kollet S.J., Maxwell R.M. Patterns and dynamics of river-aquifer exchange with variably-saturated flow using a fully-coupled model. J. Hydrol. 2009, 375:383-393.
Goderniaux P., Impact of climate change on groundwater reserves, PhD thesis, 2010, Université de Liège.
Goderniaux P., Brouyère S., Fowler H., Blenkinsop S., Therrien R., Orban Ph., Dassargues A. Large scale surface-subsurface hydrological model to assess climate change impacts on groundwater reserves. J. Hydrol. 2009, 373(1-2):122-138.
Goderniaux P., Brouyère S., Blenkinsop S., Burton A., Fowler H., Orban Ph., Dassargues A. Modeling climate change impacts on groundwater resources using transient stochastic climatic scenarios. Water Resour. Res. 2011, 47(W12516).
Graham D., Kilde L., MIKE-SHE users guide, manual, 2002, Danish Hydraulic Institute.
Gupta H., Sorooshian S., Yapo P. Status of automatic calibration for hydrologic models: comparison with multilevel expert calibration. J. Hydrol. Eng. 1999, 4(2):135-143.
Gupta H., Kling H., Yilmaz K., Martinez G. Decomposition of the mean squared error and NSE performance criteria: implications for improving hydrological modelling. J. Hydrol. 2009, 377(1-2):80-91.
Hill, M.C., 1992. A computer program (MODFLOWP) for estimating parameters of a transient, three-dimensional, ground-water flow model using nonlinear regression. Open-File Report 91-484, US Geological Survey.
Hill M.C., Cooley R., Pollock D. A controlled experiment in groundwater flow model calibration using nonlinear regression. Ground Water 1998, 36(3):520-535.
Hill M.C., Tiedeman C.R. Effective Groundwater Model Calibration with Analysis of Sensitivities, Predictions and Uncertainty 2007, John Wiley & Sons, Hoboken, NJ, USA.
Hornberger M., Raffensperger J., Wilberg P., Eshleman K. Elements of physical hydrology, Baltimore 1998, Johns Hopkins University Press, MD, USA.
Islam M., Automated calibration of a physically-based hydrologic model to simulate water balance variables for water and crop management, PhD thesis, 2004, University of California at Davis.
Irvine D.J., Brunner P., Hendricks Franssen H.-J., Simmons C.T. Heterogeneous or homogeneous? Implications of simplifying heterogeneous streambeds in models of losing streams. J. Hydrol. 2012, 424-425:16-23.
Jones J., Simulating hydrologic systems using a physically-based surface-subsurface model: issues concerning flow, transport and parameterization, PhD thesis, 2005, University of Waterloo.
Kristensen K.J., Jensen S.E. A model for estimating actual evapotranspiration from potential evapotranspiration. Nord. Hydrol. 1975, 6:170-188.
Legates D., McCabe G. Evaluating the "goodness-of-fit" measures in hydrologic and hydroclimate model validation. Water Resour. Res. 1999, 35(1):233-241.
Li Q., Unger A., Sudicky E., Kassenaar D., Wexler E., Shikaze S. Simulating the multi-seasonal response of a large-scale watershed with a 3D physically-based hydrologic model. J. Hydrol. 2008, 357(3-4):317-336.
McCuen R. Hydrologic analysis and design, Englewood Cliffs 1989, Prentice Hall, NJ, USA.
Meyerhoff S.B., Maxwell R.M. Quantifying the effects of subsurface heterogeneity on hillslope runoff using a stochastic approach. Hydrogeol. J. 2011, 19:1515-1530.
Moriasi D., Arnold J., Van Liew M., Binger R., Harmel R., Veith T. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans. ASABE 2007, 50(3):885-900.
Nash J., Sutcliffe J. River flow forecasting through conceptual models I - a discussion of principles. J. Hydrol. 1970, 10(3):282-290.
Poeter E.P., McKenna S. Reducing uncertainty associated with ground-water flow and transport predictions. Ground Water 1995, 33(6):899-904.
Panday S., Huyakorn P. A fully coupled physically-based spatially-distributed model for evaluating surface/subsurface flow. Advances in Water Resources 2004, 27(4):361-382.
Poeter E.P., Hill M.C. Inverse models: a necessary next step in ground-water modeling. Ground Water 1997, 35(2):250-260.
Radcliffe A., Physical hydrogeology and the impact of urbanization at the Waterloo West Side: a groundwater modeling approach, PhD thesis, 2000, University of Waterloo.
Ramos da Silva M., Schroeder C., Verbrugge J.-C. Unsaturated rock mechanics applied to a low-porosity shale. Eng. Geol. 2008, 97(1-2):42-52.
Refsgaard J.C. Parameterisation, calibration and validation of distributed hydrological models. J. Hydrol. 1997, 198:69-97.
Refsgaard J.C., Henriksen H. Modelling guidelines - terminology and guiding principles. Adv. Water Resour. 2004, 27(1):71-82.
Roulier S., Baran N., Mouvet C., Stenemo F., Morvan X., Albrechtsen H.-J., Clausen L., Jarvis N. Controls of atrazine leaching through a soil-unsaturated fractured limestone sequence at Brévilles. France, Journal of Contaminant Hydrology 2006, 84(1-2):81-105.
Schäfer D., Schlenz B., Dahmke A. Evaluation of exploration and monitoring methods for verification of natural attenuation using the virtual aquifer approach. Biodegradation 2004, 15(6):453-465.
Schroeder P., Aziz N., Lloyd C., Zappi P., The Hydrologic Evaluation of Landfill Performance (HELP) model: user's guide for version 3, EPA/600/R-94/168a, 1994, US EPA.
Sciuto G., Diekkrüger B. Influence of soil heterogeneity and spatial discretization on catchment water balance modeling. Vadose Zone J. 2010, 9:955-969.
Skahill B., Doherty J. Efficient accommodation of local minima in watershed model calibration. J. Hydrol. 2006, 329(1-2):122-139.
Therrien, R., McLaren, R., Sudicky, E., Park, Y.-J., 2012. HydroGeoSphere - A Three-Dimensional Numerical Model Describing Fully-integrated Subsurface and Surface Flow and Solute Transport. Manual, Groudnwater Simulations Group.
Vázquez R.F., Feyen L., Feyen J., Refsgaard J.C. Effect of grid size on effective parameters and model performance of the MIKE-SHE code. Hydrol. Process. 2002, 16:355-372.
Vogel H.-J., Ippisch O. Estimation of a critical spatial discretization limit for solving Richards' equation at large scales. Vadose Zone Journal 2008, 7(1):112-114.
Weglarczyk S. The interdependence and applicability of some statistical quality measures for hydrological models. J. Hydrol. 1998, 206(1-2):98-103.