Page 64

Presentation Title: Application of Artificial Neural Networks for Forecasting Groundwater Levels Following a Dam Removal, Milltown Montana Discipline: Hydrology School: Salish Kootenai College Presentation Type: Poster Presentation Abstract: Application of Artificial Neural Networks for Forecasting Groundwater Levels Following a Dam Removal, Milltown Montana Ashley M. Marks, Salish Kootenai College

Fifty percent of the world’s population depends upon groundwater as their main source of drinking water. One quarter of the world’s people live in areas characterized by physical water scarcity, making competition for water resources. Scarcity of groundwater affects the entire world. Tools that forecast groundwater levels have been progressively developed over time, from the Boussinesq equation in 1871 to present day. However, complex 3D numerical flow models are the standard for determining groundwater behavior in most settings and often require excessive fieldwork, data collection, expense, and computational expertise. Artificial Neural Networks (ANNs) have been successfully used in other disciplines as a more practical and cost effective alternative for predicting outcomes dependent on multiple, complex, varying inputs. This research investigates the utility of ANNs to forecast groundwater levels from common data acquired on national databases. Groundwater derived domestic water supplies were recently affected by the removal of the 28 ft Milltown Dam in Montana. A temporary 12 ft drawdown resulted in the drying of many wells. This prompted a one million dollar well replacement response by the EPA to proactively protect water supplies in the 500+ domestic wells proximal to the reservoir. ANN’s can be an invaluable tool for forecasting groundwater behavior and this study has successfully applied them to predict groundwater levels with the same accuracy as standard 3D modeling. This research shows managers that an effective strategy to forecast groundwater wells following a dam removal would be to initially use a planned drawdown in combination with an ANN.

Presenter: Ashley M. Marks Tribe: Choctaw Primary Email: ashleymarks@student.skc.edu Biography Ashley Marks is a junior in the Hydrology Program at SKC. Ashley is also the president of the newly reestablished AISES chapter at SKC, she hopes to start the chapter back up and keep it going for future students. Ashley has worked on her project now for over a year and a half and is very proud of her work.

63

2011 National Conference Student Research Abstracts  

A comprehensive list of the student research topics that will be presented at the AISES 2011 National Conference

2011 National Conference Student Research Abstracts  

A comprehensive list of the student research topics that will be presented at the AISES 2011 National Conference

Advertisement