Modeling Saltwater Upcoming with Artificial Neural Networks

摘要：

Salt-water upcoming and intrusion into freshwater groundwater systems can result in serious water quality problems, affecting potable supplies in coastal areas around the world. In this study, artificial neural networks (ANN) were developed to accurately predict highly time-variable specific conductance values in a real-world unconfined coastal aquifer. Unlike physical-based models, which require hydrologic parameter inputs, such as horizontal and vertical hydraulic conductivities and porosity, ANNs can learn system behavior from easily measurable variables. In this study, the ANN input predictor variables were the initial specific conductance (a measure of dissolved ions) measured at a monitor well, total precipitation, mean daily temperature, and total pumping extraction. The ANNs predicted conductance at a single monitoring well located near a high capacity municipal-supply well over time periods ranging from 30 days to several years.Model accuracy was compared against measured/interpolated values and predictions made with linear regression (LR), and in general, achieved excellent prediction accuracy. The ANNs were also used to conduct a sensitivity analysis that quantified the importance of each of the four predictor variables on final conductance values, providing valuable insights into the dynamics of the system. The results demonstrate that the ANNs technology can serve as a powerful and accurate prediction and management tool, minimizing degradation of ground-water quality to the extent possible by identifying appropriate pumping policies under variable groundwater system and weather conditions.

关键词： Artificial neural networks saltwater intrusion saltwater upconing groundwater management groundwater protection

作者: Emery-Coppola Ferenc-Szdarovszky Charles-Mclane Mary-Poulton Robin-Magelky

作者单位: NOAH, L. L. C. , 610 Lawrence Road, Lawrenceville , New Jersey, 08648-4208 U.S.A Department of Systems and Industrial Engineering, University of Arizona, Tucson, Arizona, &5721-0020 McLane Environmental L.L.C.,707 Alexander Road,Suite 206,Princeton,New Jersey 08540-6331 U.S.A Department of Mining and Geological Engineering,University of Arizona,Tucson,Arizona,85721 - 0012 U.

会议类型: 国际会议

会议名称: International Conference on Effective Utilization of Agricultural Soil & Water Resources and Protection of Environment and the 4th Annual Academic Conference of Chinese Society of Agricultural Soil and Water Engineering

会议地点: 南京

会议语种:英文

页码: 3-8

在线出版日期: 2006-08-16（万方平台首次上网日期，不代表论文的发表时间）