Systems Analysis in Ground‐Water Planning and Management

Abstract

The objective of this paper is to review the state of the art of systems analysis and optimization techniques developed in the field of water resources for the planning and management of a ground‐water system. The areas reviewed include the following: ground‐water management models, inverse solution techniques for parameter identification, and optimal experimental design methods. Emphasis is placed upon ground‐water supply management models, as opposed to models used for ground‐water quality management. The techniques that have been used in the optimization of ground‐water management include: linear programming, mixed‐integer and quadratic programming, differential dynamic programming, nonlinear programming, and simulation. The inverse problem of parameter identification pertains the optimal determination of model parameters using historical input and output observations. Because of data limitation in both quantity and quality, the inverse problem is inherently ill posed. This paper summarizes recent advances made in the inverse procedures and methods developed to alleviate the problems of instability ard nonuniqueness of the identified parameters. The optimal experimental design problem addresses the issue of data requirements and optimal sampling strategies for the purpose of parameter identification. A criterion must be established for the optimal design of a pumping test. The fundamental concept of optimal experimental design and various criteria used for optimization are reviewed.