HR: 14:40h
AN: H33M-05    [Abstracts]
TI: Adaptive Management of Remediation Systems Under Uncertain Hydraulic Conductivity and Plume Distribution
AU: * Bau, D A
EM: domenico.bau@colostate.edu
AF: Dept. of Civil and Environmental Engineering, Colorado State University, 1372 Campus Delivery, Fort Collins, CO 80525, United States
AU: Mayer, A S
EM: asmayer@mtu.edu
AF: Dept. of Geological & Mining Engineering & Sciences, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931, United States
AB: The optimal design and the management of pump-and-treat (PAT) remediation systems is generally tackled with the aid of combined simulation-optimization models to rank alternatives while considering management objectives and constraints. Since this process is typically carried out in an environment of uncertainties, our ability to determine cleanup policies that are cost optimal and reliable at the same time is in fact limited. In this work, we present a stochastic optimal control framework for assisting the management of the PAT cleanup of polluted shallow aquifers. Hydraulic conductivity distribution and dissolved contaminant plume location are considered as the uncertain parameters. The framework considers the subdivision of the cleanup horizon in a sequence of stress periods over which the pumping policy implemented at each stage is dynamically adjusted based on new information that has become available in the previous stages. In particular, we study the idea of monitoring the cumulative contaminant mass extracted from the installed recovery wells, and using these measurements to generate conditional realizations of the hydraulic conductivity field. These realizations are thus used to obtain a more accurate evaluation of the initial plume distribution, and modify accordingly the design of the PAT system for the remainder of the remedial process. The study indicates that measurements of contaminant mass extracted from pumping wells retain valuable information about the plume location and the spatial heterogeneity characterizing the hydraulic conductivity field. However, such an information may prove quite soft, particularly in the instances where recovery wells are installed in regions where contaminant concentration is low or zero. On the other hand, integrated solute mass meausurements may effectively allow for reducing parameter uncertainty and identifying the plume distribution if more recovery wells are available, in particular in the early stages of the cleanup process.
DE: 1828 Groundwater hydraulics
DE: 1829 Groundwater hydrology
DE: 1847 Modeling
DE: 1869 Stochastic hydrology
SC: Hydrology [H]
MN: 2007 Fall Meeting