Volume 6 Issue 4
Oct.  2013
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Zhong-wei ZHAO, Jian ZHAO, Chang-sheng FU. 2013: Uncertainty analysis of seawater intrusion forecasting. Water Science and Engineering, 6(4): 380-391. doi: 10.3882/j.issn.1674-2370.2013.04.002
Citation: Zhong-wei ZHAO, Jian ZHAO, Chang-sheng FU. 2013: Uncertainty analysis of seawater intrusion forecasting. Water Science and Engineering, 6(4): 380-391. doi: 10.3882/j.issn.1674-2370.2013.04.002
shu

Uncertainty analysis of seawater intrusion forecasting

doi: 10.3882/j.issn.1674-2370.2013.04.002
  • 1.

    State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University,

  • 2.

    College of Water Conservancy and Hydropower Engineering, Hohai University,

  • 3.

    Jiangsu Provincial Communication Planning and Design Institute, Nanjing 210005, P. R. China

Funds:  This work was supported by the National Natural Science Foundation of China (Grant No. 51309091) and the Environmental Protection Foundation of Jiangsu Province (Grant No. 2010080).
More Information
  • Corresponding author: Jian ZHAO
  • Received Date: 2012-08-03
  • Rev Recd Date: 2013-03-19
    Abstract
  •  In order to describe the importance of uncertainty analysis in seawater intrusion forecasting and identify the main factors that might cause great differences in prediction results, we analyzed the influence of sea level rise, tidal effect, the seasonal variance of influx, and the annual variance of the pumping rate, as well as combinations of different parameters. The results show that the most important factors that might cause great differences in seawater intrusion distance are the variance of pumping rate and combinations of different parameters. The influence of sea level rise can be neglected in a short-time simulation (ten years, for instance). Retardation of seawater intrusion caused by tidal effects is obviously important in aquifers near the coastline, but the influence decreases with distance away from the coastline and depth away from the seabed. The intrusion distance can reach a dynamic equilibrium with the application of the sine function for seasonal effects of influx. As a conclusion, we suggest that uncertainty analysis should be considered in seawater intrusion forecasting, if possible.   

     

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    • References(23)
  • Bear, J., and Cheng, A. H. D. 2008. Modeling Groundwater Flow and Contaminant Transport. New York: Springer Verlag.
    Binley, A., Buckley, K., Calore, C., Parodi, U., and La Barbera, P. 1997. Modelling uncertainty in estimates of recharge to a shallow coastal aquifer. Hydrological Sciences Journal, 42(2), 155-168.
    Box, G. E. P., Hunter, J. S., and Hunter, W. G. 2005. Statistics for Experimenters: Design, Innovation, and Discovery. New York: Wiley-Interscience.
    Chen, Z., Huang, G. H., and Chakma, A. 2003. Hybrid fuzzy-stochastic modeling approach for assessing environmental risks at contaminated groundwater systems. Journal of Environmental Engineering, 129(1), 79-88. [doi: 10.1061/(ASCE)0733-9372(2003)129:1(79)]
    Dagan, G., and Zeitoun, D. G. 1998. Seawater-freshwater interface in a stratified aquifer of random permeability distribution. Journal of Contaminant Hydrology, 29(3), 185-203. [doi:10.1016/S0169- 7722(97)00013-2]
    Dhar, A., and Datta, B. 2009a. Saltwater intrusion management of coastal aquifers, I: Linked simulation- optimization. Journal of Hydrologic Engineering, 14(12), 1263-1272. [doi:10.1061/(ASCE)HE.1943- 5584.0000097]
    Dhar, A., and Datta, B. 2009b. Saltwater intrusion management of coastal aquifers, II: Operation uncertainty and monitoring. Journal of Hydrologic Engineering, 14(12), 1273-1282. [doi:10.1061/(ASCE)HE.1943- 5584.0000155]
    Gelhar, L. W., Welty, C., and Rehfeldt, K. R. 1992. A critical-review of data on field-scale dispersion in aquifers. Water Resources Research, 28(7), 1955-1974. [doi: 10.1029/92WR00607]
    Glover, R. 1959. The pattern of fresh-water flow in a coastal aquifer. Journal of Geophysical Research, 64(4), 457-459. [doi: 10.1029/JZ064i004p00457]
    Herckenrath, D., Langevin, C. D., and Doherty, J. 2011. Predictive uncertainty analysis of a saltwater intrusion model using null-space Monte Carlo. Water Resources Research, 47(5). [doi: 10.1029/2010WR009342]
    Konikow, L. F. 2010. The secret to successful solute-transport modeling. Ground Water, 49(2), 144-159. [doi: 10.1111/j.1745-6584.2010.00764.x]
    Lecca, G., and Cau, P. 2009. Using a monte carlo approach to evaluate seawater intrusion in the Oristano coastal aquifer: A case study from the AQUAGRID collaborative computing platform. Physics and Chemistry of the Earth, 34(10-12), 654-661. [doi: 10.1016/j.pce.2009.03.002]
    Loaiciga, H. A., Pingel, T. J., and Garcia, E. S. 2012. Sea water intrusion by sea-level rise: Scenarios for the 21st century. Ground Water, 50(1), 37-47. [doi: 10.1111/j.1745-6584.2011.00800.x]
    Ministry of Land and Resource of the People’s Republic of China (MLRPRC). 2010. Communique of Sea Level in China. Beijing: MLRPRC.
    Narayan, K. A., Schleeberger, C., and Bristow, K. L. 2007. Modelling seawater intrusion in the Burdekin Delta Irrigation Area, North Queensland, Australia. Agricultural Water Management, 89(3), 217-228. [doi: 10.1016/j.agwat.2007.01.008]
    Nicholls, R. J., and Cazenave, A. 2010. Sea-level rise and its impact on coastal zones. Science, 328(5985) 1517-1520.
    Qin, X. S., and Huang, G. H. 2009. Characterizing uncertainties associated with contaminant transport modeling through a coupled fuzzy-stochastic approach. Water, Air, and Soil Pollution, 197(1-4), 331-348. [doi: 10.1007/s11270-008-9815-8]
    Robinson, C., Li, L., and Barry, D. A. 2007. Effect of tidal forcing on a subterranean estuary. Advances in Water Resources, 30(4), 851-865. [doi: 10.1016/j.advwatres.2006.07.006]
    Sanford, W. E., and Pope, J. P. 2010. Current challenges using models to forecast seawater intrusion: Lessons from the Eastern Shore of Virginia, USA. Hydrogeology Journal, 18(1), 73-93. [doi:10.1007/s10040- 009-0513-4]
    Schincariol, R. A., Schwartz, F. W., and Mendoza, C. A. 1994. On the generation of instabilities in variable density flow. Water Resources Research, 30(4), 913-927. [doi: 10.1029/93WR02951]
    Sreekanth, J., and Datta, B. 2011. Coupled simulation-optimization model for coastal aquifer management using genetic programming-based ensemble surrogate models and multiple-realization optimization. Water Resources Research, 47(4). [doi: 10.1029/2010WR009683]
    United States Environmental Protection Agency (USEPA). 1976. Quality Criteria for Water. Washington, D. C.: USEPA.
    Voss, C. I., and Provost, A. M. 2010. SUTRA, A Model for Saturated-Unsaturated, Variable-Density Ground-Water Flow with Solute or Energy Transport, Water-Resources Investigations Report 02-4231. Reston: U.S. Geological Survey.
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