Global Sensitivity Analysis of a Coastal Groundwater Simulation Model Using Five Methods (Lahijan-Chaboksar Aquifer)

Document Type : Research Paper

Authors

1 Water Resources Engineering Dept., Tarbiat Modares University, Tehran, Iran

2 Assistant Professor, Water Resources Engineering Dept., Tarbiat Modares University, Tehran, Iran

Abstract

Water supply from groundwater resources because of rapid population growth and coastal zones development, converts the intensity of seawater intrusion to a global concern in these areas. Analyzing the sensitivity of costal aquifers' behavior to different controlling factors, preventing the seawater intrusion to these resources and the related adverse consequences is an essential effort. This study aimed to analyze the global sensitivity of factors controlling the seawater intrusion and the interaction of Caspian Sea water and the considered coastal aquifer.
To assess the seawater intrusion, SUTRA, a three-dimensional density-dependent calibrated and validated numerical model, was employed. For this purpose, five well-known global sensitivity analysis methods have been employed and the sensitivity indices of each methods have been calculated. The permeability of first layer was the most sensitive parameter based on FAST, VBSA, PAWN and RSA methods among five considered methods. The fifth layer’s permeability was found to be the most sensitive parameter by applying EE. Overall, the higher the permeability of extended layers nearer to coastline, the larger the seawater intrusion. Therefore, the permeability of such layers effectively contributes to seawater intrusion. These findings can be used to support the management-related decisions and prioritize the measurements conducted on the aquifer in the study area. Such decisions are not based on the local findings and consider all possible changes of layers' permeability, therefore cause to more reliability.

Keywords

Main Subjects


Chun, J.A., Lim, C., Kim, D., Kim, J.S. (2018). assessing impacts of climate change and sea-level rise on seawater intrusion in a coastal aquifer. Water 10(4), 357-368.
Confalonieri, R., Bellocchi, G., Bregaglio, S., Donatelli, M., Acutis, M. (2010). Comparison of sensitivity analysis techniques: A case study with the rice model WARM. Ecological Modelling 221(16), 1897-1906.
Cukier, R., Levine, H., Shuler, K. (1978). Nonlinear sensitivity analysis of multiparameter model systems. Journal of computational physics 26(1), 1-42.
Ganji, A., Maier, H.R., Dandy, G.C. (2016). A modified sobol′ sensitivity analysis method for decision-making in environmental problems. Environmental Modelling and Software 75, 15-27.
Hamraz, B.S., Akbarpour, A., Pourreza Bilondi, M. (2016). Assessment of parameter uncertainty of modflow model using glue method (case study: birjand plain). Journal of Water and Soil Conservation 22(6), 61-79 (In Farsi)
Helton, J.C., Davis, F.J. (2000). Sampling-based methods for uncertainty and sensitivity analysis, Sandia National Labs., Albuquerque, NM (US); Sandia National Labs.
Iran Water Resources Management Company (2016) Updating water resources studies report of Lahijan-Chaboksar subbasin, Ministry of Energy, Mazandaran Regional Water Authority, Technical Report. (In Farsi)
Karatzas, GP., Dokou, Z. (2015). Optimal management of saltwater intrusion in the coastal aquifer of malia, crete (greece), using particle swarm optimization. Hydrogeology Journal 23(6), 1181-1194.
Kazemi, H., Ketabchi, H., Mohammad-Vali-Samani, J. (2019). Numerical simulation of lahijan-chaboksar coastal aquifer: investigating the possible future scenarios. Iranian Journal of Soil and Water Research 1-17 (In Farsi).
Ketabchi, H., and Ataie-Ashtiani, B. (2011). Development of combined ant colony optimization algorithm and numerical simulation for optimal management of coastal aquifers. Iran-Water Resources Research, 7(1), 1-12. (In Farsi).
Ketabchi, H., Ataie-Ashtian, B. (2015). Evolutionary algorithms for the optimal management of coastal groundwater: a comparative study toward future challenges. Journal of Hydrology 520,193-213.
Khorashadi Zadeh, F., Nossent, J., Sarrazin, F., Pianosi, F., van Griensven, A., Wagener, T., Bauwens, W. (2017). Comparison of variance-based and moment-independent global sensitivity analysis approaches by application to the swat model. Environmental Modelling and Software 91, 210-222.
Lathashri, U.A., Mahesha, A. (2016). Predictive simulation of seawater intrusion in a tropical coastal aquifer. Journal of Environmental Engineering 142(12), D4015001.
Mahmoodzadeh, D., Ketabchi, H., Ataie-Ashtiani, B. (2016). Effects of Sea Level Rise and Recharge Rate Variations on Seawater Intrusion in Confined Aquifer. Journal of Hydraulics 10(4), 1-15.
Makler-Pick, V., Gal, G., Gorfine, M., Hipsey, M.R., Carmel, Y. (2011). Sensitivity analysis for complex ecological models – A new approach. Environmental Modelling and Software 26(2), 124-134.
Nakhaei, M., Vadiati, M. (2014). Spatial analysis of natural hazards resulting from the over- exploration of ground water in the coastal aquifer of urmia region. Journal of Spatial Analysis Environmental Hazarts 1(1), 53-65 (In Farsi).
Pianosi, F., Beven, K., Freer, J., Hall, J.W., Rougier, J., Stephenson, D.B., Wagener, T. (2016). Sensitivity analysis of environmental models: a systematic review with practical workflow. Environmental Modelling and Software 79, 214-232.
Pianosi, F., Sarrazin, F., Wagener, T. (2015). A Matlab toolbox for Global Sensitivity Analysis. Environmental Modelling and Software 70, 80-85.
Pianosi, F., Wagener, T. (2015). A simple and efficient method for global sensitivity analysis based on cumulative distribution functions. Environmental Modelling and Software 67, 1-11.
Rajabi, M.M., Ataie-Ashtiani, B., Simmons, C.T. (2015). Polynomial chaos expansions for uncertainty propagation and moment independent sensitivity analysis of seawater intrusion simulations. Journal of Hydrology 520, 101-122.
Saghi-Jadid, M., Ketabchi, H. (2019). Restoration management of groundwater resources using the combined model of numerical simulation - evolutionary ant colony optimization. Iran Water Resources Research 15(2), 119-133. (In Farsi).
Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., Tarantola, S. (2008). Global sensitivity analysis: the primer. John Wiley and Sons
Saltelli, A., Tarantola, S., Campolongo, F. (2000). Sensitivity Anaysis as an Ingredient of Modeling. Statist. Sci. 15(4), 377-395.
Sobol, I.M. (2001). Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates. Mathematics and computers in simulation 55(1-3), 271-280.
Voss, C.I., and Provost, A.M. (2010). SUTRA: A model for saturated-unsaturated, variable-density groundwater flow with solute or energy transport. USGS Water Resources Investigations Report, 2002-4231.
Voss, C.I., Souza, W.R. (1987). Variable density flow and solute transport simulation of regional aquifers containing a narrow freshwater-saltwater transition zone. Water Resources Research, 23(10), 1851-1866.
Xu, C., Gertner, G. (2007). Extending a global sensitivity analysis technique to models with correlated parameters. Computational Statistics and Data Analysis 51(12), 5579-5590.