HR: 1340h
AN: H23E-1469    [Abstracts]
TI: Optimization of monitoring network for identification of contaminant plume distribution
AU: * Kim, K
EM: raxia99@gmail.com
AF: Seoul National University, NS80 School of Earth & Environmental Sciences College Natural Sciences Seoul National University, Seoul, 151-742 Korea, Republic of
AU: Lee, K
EM: kklee@snu.ac.kr
AF: Seoul National University, NS80 School of Earth & Environmental Sciences College Natural Sciences Seoul National University, Seoul, 151-742 Korea, Republic of
AB: A new methodology to optimize monitoring network for identification of contaminant plume distribution is proposed. The optimal locations for monitoring wells are determined to the expected point that maximizes decreasing of the quantified uncertainty about contaminant existence after well installation. In this study, hydraulic conductivity is considered to be the factor making uncertainty. Successive Random Addition (SRA) method is used to generate hydraulic conductivity random fields. The expected value of data information of each monitoring network is evaluated based on how much uncertainty of plume distribution reduces with the monitoring network. The array of monitoring wells having the maximum data information is selected as the optimal monitoring network. In order to quantify uncertainty of the plume distribution, the probability map of contaminant existence is made for all generated plume realizations on the domain field and the uncertainty is defined as the area that probability range is neither 0 nor 1. Using proposed methodology, efficiencies of four monitoring networks are evaluated. Numerical experiment results present that in homogeneous hydraulic conductivity model, the monitoring network in which monitoring wells are located on the direction of groundwater flow in a line is the most efficient. One the other hand, in heterogeneous hydraulic conductivity model, the case that the monitoring wells are located both on the direction of groundwater flow and the transverse direction to groundwater flow is the most efficient.
DE: 1831 Groundwater quality
DE: 1848 Monitoring networks
SC: Hydrology [H]
MN: Fall Meeting 2005