Groundwater management under uncertainty using a stochastic multi-cell model

Ata Joodavi, Mohammad Zare, Ali Naghi Ziaei, Ty P.A. Ferré

Research output: Research - peer-reviewArticle

Abstract

The optimization of spatially complex groundwater management models over long time horizons requires the use of computationally efficient groundwater flow models. This paper presents a new stochastic multi-cell lumped-parameter aquifer model that explicitly considers uncertainty in groundwater recharge. To achieve this, the multi-cell model is combined with the constrained-state formulation method. In this method, the lower and upper bounds of groundwater heads are incorporated into the mass balance equation using indicator functions. This provides expressions for the means, variances and covariances of the groundwater heads, which can be included in the constraint set in an optimization model. This method was used to formulate two separate stochastic models: (i) groundwater flow in a two-cell aquifer model with normal and non-normal distributions of groundwater recharge; and (ii) groundwater management in a multiple cell aquifer in which the differences between groundwater abstractions and water demands are minimized. The comparison between the results obtained from the proposed modeling technique with those from Monte Carlo simulation demonstrates the capability of the proposed models to approximate the means, variances and covariances. Significantly, considering covariances between the heads of adjacent cells allows a more accurate estimate of the variances of the groundwater heads. Moreover, this modeling technique requires no discretization of state variables, thus offering an efficient alternative to computationally demanding methods.

LanguageEnglish (US)
Pages265-277
Number of pages13
JournalJournal of Hydrology
Volume551
DOIs
StatePublished - Aug 1 2017

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groundwater
method
aquifer
groundwater flow
recharge
modeling
groundwater abstraction
water demand
mass balance
simulation
parameter
indicator
comparison
distribution

Keywords

  • Constrained-state formulation
  • Lumped-parameter aquifer model
  • Stochastic optimization
  • Uncertainty

ASJC Scopus subject areas

  • Water Science and Technology

Cite this

Groundwater management under uncertainty using a stochastic multi-cell model. / Joodavi, Ata; Zare, Mohammad; Ziaei, Ali Naghi; Ferré, Ty P.A.

In: Journal of Hydrology, Vol. 551, 01.08.2017, p. 265-277.

Research output: Research - peer-reviewArticle

Joodavi, Ata ; Zare, Mohammad ; Ziaei, Ali Naghi ; Ferré, Ty P.A./ Groundwater management under uncertainty using a stochastic multi-cell model. In: Journal of Hydrology. 2017 ; Vol. 551. pp. 265-277
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