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Approximating the optimal groundwater pumping policy in a multiaquifer stochastic conjunctive use setting
Author(s) -
Provencher Bill,
Burt Oscar
Publication year - 1994
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/93wr02683
Subject(s) - aquifer , dynamic programming , conjunctive use , mathematical optimization , monte carlo method , groundwater , yield (engineering) , bellman equation , mathematics , function (biology) , stochastic programming , computer science , geology , geotechnical engineering , physics , statistics , thermodynamics , evolutionary biology , biology
This paper presents two methods for approximating the optimal groundwater pumping policy for several interrelated aquifers in a stochastic setting that also involves conjunctive use of surface water. The first method employs a policy iteration dynamic programming (DP) algorithm where the value function is estimated by Monte Carlo simulation combined with curve‐fitting techniques. The second method uses a Taylor series approximation to the functional equation of DP which reduces the problem, for a given observed state, to solving a system of equations equal in number to the aquifers. The methods are compared using a four‐state variable, stochastic dynamic programming model of Madera County, California. The two methods yield nearly identical estimates of the optimal pumping policy, as well as the steady state pumping depth, suggesting that either method can be used in similar applications.