Characterizing Groundwater Contamination Before and During Remediation

这一奖项旨在支持在系统地考虑污染源的可变性和不确定性的情况下预测地下水污染物羽流运动的研究。场地表征程序可用于在修复开始前评估污染的程度和严重程度，并在修复期间评估进展情况。将要开发的程序以贝叶斯估计技术为基础，该技术将现场测量与随机地下水模型的预测相结合，该模型提供了整个受污染地点溶质浓度的平均值和方差的估计只要有新的水力导电性、压头和/或污染物浓度测量数据可用，这些数据就会进行修订。本研究与NSF资助项目85-14987有关。它补充了研究人员在国家环境卫生科学研究所的支持下正在进行的实地研究，以确定吸附在从地下水中去除污染物方面的作用。预计该项目的成果将用于改善净化地下水含水层的工程设计和系统的操作。

This is an award to support research on predicting the motion of groundwater contaminant plumes taking systematically into account the variability and uncertainties about the source of the contamination. The site characterization procedure may be used to assess the extent and severity of contamination before remediation begins and to evaluate progress during remediation. The procedure to be developed is based on Bayesian estimation techniques that combine field measurements with predictions from a stochastic groundwater model that provides estimates of the mean and variance of solute concentration throughout a contaminated site that are revised whenever new measurements of hydraulic conductivity, pressure head and/or contaminant concentration become available. This research is related to a project previously supported under NSF Grant No. 85-14987. It complements research the investigator is conducting with support from the National Institute of Environmental Health Sciences on field studies to characterize the role of sorption on removing contaminants from groundwater. Results of this project are expected to be used to improve the engineering design and operation of systems to decontaminate groundwater aquifers.