Abstract
This paper employs a modified penalty function and conjugate gradient based nonlinear programming algorithm to solve large integrated groundwater management problems.Discrete kernels are used to incorporate spatial and temporal distribution of the aquifer response due to external stresses. Significant improvements in computational speed and storage requirement are achieved owing to this unique conjugate gradient-discrete kernel combination. Simulations of the 'socially optimal' and 'open access' groundwater extraction schemes are presented as case studies of important policy implications.
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