Stochastically optimal considering groundwater management land subsidence

Abstract

This paper presents a stochastic groundwater management model explicitly considering land subsidence. Through the use of response matrix technique and one-dimensional consolidation equation, a deterministic management model is first developed. By Latin hypercube sampling technique, along with numerical subsurface flow simulation, statistical features of unit response coefficients due to random hydrogeologic parameters, including hydraulic conductivity (K) and Lame constants (mu and lambda), are quantified. The first-ordervariance-estimation method is adopted to analyze the uncertainties of drawdown and land subsidence based on which the concept of chance-con strained programming is applied to transfer the original deterministic management model into its stochastic form. The stochastic management model enables the determination of optimal total pumpage subject to the constraints that drawdown and land subsidence do not exceed the allowable values with a specified reliability. A hypothetical example is utilized to demonstrate the applicability of the stochastic model to five cases in which various levels of parameter uncertainty are considered. The results indicate that joint consideration of drawdown and land subsidence is essential, and the proposed stochastic management model can be generally applied for regional groundwater resources management in conjunction with controlling land subsidence.