Least-Cost Groundwater Remediation Design Using Uncertain Hydrogeological Information

Pinder, George F.

University of Vermont, Burlington, Vermont (United States)

关键词: Management;    Algorithms;    Mathematical Models;    Design;    58 Geosciences;   

DOI  :  10.2172/828510
RP-ID  :  EMSP-60069--2000
RP-ID  :  GF07-97ER62525
RP-ID  :  828510

美国|英语

来源: UNT Digital Library

【 摘 要 】

The main objective of this research is to develop a computer code that will facilitate design of robust risk based pump and treat groundwater remediation and management systems. The resulting systems will operate under both gradient and concentration constraints. The design is a least cost design. The element of risk in the remediation design considered in this work is that due to the uncertainty in the hydraulic conductivity of the contaminated aquifer in question. Considerable work has been done in the field of optimal groundwater remediation and management design. Existent design algorithms depend upon the reliability of the groundwater flow and transport models to predict the movement of contamination in a given aquifer. The reliability of these mathematical models is, in turn, dependent upon variables that describe the physical attributes of the aquifer in question. The hydraulic conductivity of the aquifer is the most influential of the state variables that are used to de scribe groundwater flow and transport. Many models assume the hydraulic conductivity is known with certainty. However, field data shows that the hydraulic conductivity is uncertain An immediate goal of this research is to successfully apply a new method of optimization to incorporate uncertainty in hydraulic conductivity into the groundwater remediation design subject to gradient and concentration constraints. In doing this, a new method of sampling uncertainty distributions has been formulated and successfully implemented. A new method of solving nonconvex optimization problems has also been successfully developed and applied. This method, called the tunneling method, is an efficient technique for solving optimization problems where multiple interior local minimum values exist in the feasible region (3). The results of this work provide a tool to create cost-effective design-risk-based groundwater-management systems.