Technical Papers
May 29, 2013

Global Sensitivity Analysis of Variably Saturated Flow and Transport Parameters and Its Implication for Crop Yield and Root Zone Hydrosalinity

Publication: Journal of Irrigation and Drainage Engineering
Volume 139, Issue 11

Abstract

Modeling of crop yield and root zone hydrosalinity usually requires a large number of parameters that are often expensive to obtain and have associated measurement errors. Consequently, identifying the most relevant parameters, and their contributions to the uncertainty of the output, might be utilized as a basis to focus research resources efficiently. Global sensitivity analysis (GSA) is a powerful tool that can be utilized to achieve this goal. However, some GSA methods perform better than others, which introduces the risk of mistakenly prioritizing a secondary parameter while neglecting a primary one. This paper evaluates four GSA methods utilized to rank the importance of a total of 18 input parameters with respect to five performance indices using a variable saturated flow and transport model. Some of the major findings of this research are (1) the crop-yield variance is controlled largely by only four of the 18 parameters that were considered in this study; (2) the van Genuchten pore-size parameter was found to be very important to the relative crop-yield prediction and the water-availability index; and (3) the variance-decomposing method, the screening method, and the Monte Carlo–filtering method are generally consistent in their performance, whereas the partial-correlation coefficient method is significantly different.

Get full access to this article

View all available purchase options and get full access to this article.

Acknowledgments

This work was partially funded by a project from the U. S. Bureau of Reclamation, and the authors are grateful for the help provided by Mr. Roger Burnett, an agricultural engineer with the U. S. Bureau of Reclamation, Denver Technical Services Center.

References

Ahlfeld, D. P., and Mulligan, A. E. (2000). Optimal management of flow in groundwater systems: An introduction to combining simulation models and optimization methods, Academic Press, Orlando, FL.
Alzraiee, A., Garcia, L., and Gates, T. (2013). “Modeling subsurface heterogeneity of irrigated and drained fields. I: Model development and testing.” J. Irrig. Drain. Eng., 797–808.
Anderson, M. P., and Woessner, W. W. (1992). Applied groundwater modeling, Academic Press, Orlando, FL.
Beven, K., and Binley, A. (1992). “The future of distributed models: Model calibration and uncertainty prediction.” Hydrol. Processes, 6(3), 279–298.
Bredehoeft, J. D., and Pinder, George F. (1973). “Mass transport in flowing groundwater.” Water Resour. Res., 9(1), 194–210.
Campolongo, F., Cariboni, J., and Saltelli, A. (2007). “An effective screening design for sensitivity analysis of large models.” Environ. Model. Software, 22(10), 1509–1518.
Cardon, G. E., and Letey, J. (1992). “Plant water uptake terms evaluated for soil water and solute movement models.” Soil Sci. Soc. Am. J., 56(6), 1876–1880.
Cukier, R. I., Fortuin, C. M., Shuler, K. E., Petschek, A. G., and Schaibly, J. H. (1973). “Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I: Theory.” J. Chem. Phys., 59(8), 3873–3878.
Doherty, J., Brebber, L., and Whyte, P. (2002). “PEST: Model independent parameter estimation.” Watermark Computing, Corinda, Australia.
Feddes, R. A., Kowalik, P., Kolinska-Malinka, K., and Zaradny, H. (1976). “Simulation of field water uptake by plants using a soil water dependent root extraction function.” J. Hydrol., 31(1–2), 13–26.
Freeze, R. A. (1971). “Three-dimensional, transient, saturated–unsaturated flow in a groundwater basin.” Water Resour. Res., 7(2), 347–366.
Giglioli, N., and Saltelli, A. (2000). “SimLab 1.1, software for sensitivity and uncertainty analysis, tool for sound modelling.” 〈http://arxiv.org/ftp/cs/papers/0011/0011031.pdf〉 (Aug. 3, 2013).
Gupta, R. K., and Abrol, I. (1990). “Salt-affected soils: Their reclamation and management for crop production.” Adv. Soil Sci., 11, 223–288.
Helton, J. C. (1993). “Uncertainty and sensitivity analysis techniques for use in performance assessment for radioactive waste disposal.” Reliab. Eng. Syst. Saf., 42(2–3), 327–367.
Helton, J. C., Johnson, J. D., Sallaberry, C. J., and Storlie, C. B. (2006). “Survey of sampling-based methods for uncertainty and sensitivity analysis.” Reliab. Eng. Syst. Saf., 91(10–11), 1175–1209.
Hill, M. C., and Tiedeman, C. R. (2007). Effective groundwater model calibration: With analysis of data, sensitivities, predictions, and uncertainty, Wiley-Interscience, New York.
Homma, T., and Saltelli, A. (1996). “Importance measures in global sensitivity analysis of nonlinear models.” Reliab. Eng. Syst. Saf., 52(1), 1–17.
Jongschaap, R. E. E. (2007). “Sensitivity of a crop growth simulation model to variation in LAI and canopy nitrogen used for run-time calibration.” Ecol. Modell., 200(1–2), 89–98.
Makowski, D., Naud, C., Jeuffroy, M.-H., Barbottin, A., and Monod, H. (2006). “Global sensitivity analysis for calculating the contribution of genetic parameters to the variance of crop model prediction.” Reliab. Eng. Syst. Saf., 91(10–11), 1142–1147.
Meyer, P. D., Rockhold, M. L., and Gee, G. W. (1997). “Uncertainty analyses of infiltration and subsurface flow and transport for SDMP sites.”, U.S. Nuclear Regulatory Commission, Washington, DC.
Mishra, S., Deeds, N., and Ruskauff, G. (2009). “Global sensitivity analysis techniques for probabilistic ground water modeling.” Ground Water, 47(5), 727–744.
Morris, M. D. (1991). “Factorial sampling plans for preliminary computational experiments.” Technometrics, 33(2), 161.
Oakley, J. E., and O’Hagan, A. (2004). “Probabilistic sensitivity analysis of complex models: A Bayesian approach.” J. Roy. Stat. Soc. B. Stat. Meth., 66(3), 751–769.
Pan, F., Zhu, J., Ye, M., Pachepsky, Y. A., and Wu, Y.-S. (2011). “Sensitivity analysis of unsaturated flow and contaminant transport with correlated parameters.” J. Hydrol., 397(3–4), 238–249.
Pathak, T., Fraisse, C., Jones, J., Messina, C., and Hoogenboom, G. (2007). “Use of global sensitivity analysis for CROPGRO cotton model development.” Trans. ASABE, 50(6), 2295–2302.
Peralta, R. C. (2012). Groundwater optimization handbook: Flow, contaminant transport, and conjunctive management, CRC Press, Boca Raton, FL.
Raghuwanshi, N., and Wallender, W. (1998). “Optimization of furrow irrigation schedules, designs and net return to water.” Agric. Water Manage., 35(3), 209–226.
Ruget, F., Brisson, N., Delécolle, R., and Faivre, R. (2002). “Sensitivity analysis of a crop simulation model, STICS, in order to choose the main parameters to be estimated.” Agronomie, 22(2), 133–158.
Saltelli, A., and Bolado, R. (1998). “An alternative way to compute Fourier amplitude sensitivity test (FAST).” J. Comput. Stat. Data Anal., 26(4), 445–460.
Saltelli, A., et al. (2008). Global sensitivity analysis: The primer, Wiley-Interscience, New York.
Schaap, M. G., Leij, F. J., and van Genuchten, M. T. (2001). “Rosetta: A computer program for estimating soil hydraulic parameters with hierarchical pedotransfer functions.” J. Hydrol., 251(3–4), 163–176.
Shalhevet, J., Vinten, A., and Meiri, A. (1986). “Irrigation interval as a factor in sweet corn response to salinity.” Agron. J., 78(3), 539–545.
Sobol, I. M. (1993). “Sensitivity analysis for non-linear mathematical models.” Math. Modell. Comput. Exp., 1(1), 407–414.
Sobol, I. M. (2001). “Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates.” Math. Comput. Simul., 55(1–3), 271–280.
Trescott, P. C., Pinder, G. F., Larson, S., and Pinder, G. F. (1976). Finite-difference model for aquifer simulation in two dimensions with results of numerical experiments, U.S. Dept. of the Interior, Geological Survey, Reston, VA.
Vaccaro, J. (2007). “Deep percolation model for estimating ground-water recharge: Documentation of modules for the modular modeling system of the U.S. geological survey.” U.S. Dept. of the Interior, Geological Survey, Reston, VA.
Varella, H., Guérif, M., and Buis, S. (2010). “Global sensitivity analysis measures the quality of parameter estimation: The case of soil parameters and a crop model.” Environ. Modell. Software, 25(3), 310–319.
Veenhof, D. W., and McBride, R. A. (1994). “A preliminary performance evaluation of a soil water balance model (SWATRE) on corn producing croplands in the RM of Haldimand-Norfolk.” Soil compaction susceptibility and compaction risk assessment for corn production, Centre for Land and Biological Resources Research AAFC, Ottawa, ON, 112–142.
Xevi, E., Gilley, J., and Feyen, J. (1996). “Comparative study of two crop yield simulation models.” Agric. Water Manage., 30(2), 155–173.

Information & Authors

Information

Published In

Go to Journal of Irrigation and Drainage Engineering
Journal of Irrigation and Drainage Engineering
Volume 139Issue 11November 2013
Pages: 889 - 897

History

Received: Apr 6, 2012
Accepted: May 27, 2013
Published online: May 29, 2013
Discussion open until: Oct 29, 2013
Published in print: Nov 1, 2013

Permissions

Request permissions for this article.

Authors

Affiliations

Ayman H. Alzraiee [email protected]
Postdoctoral Fellow, Dept. of Civil and Environmental Engineering (1372), Colorado State Univ., Fort Collins, CO 80523 (corresponding author). E-mail: [email protected]
Luis A. Garcia [email protected]
M.ASCE
Director, Integrated Decision Support Group and Professor, Dept. of Civil and Environmental Engineering (1372), Colorado State Univ., Fort Collins, CO 80523. E-mail: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share