State Water Resources Research Institute Program


Project ID: 2011LA81B
Title: Feasibility Study of Scavenging Approach to Stop Saltwater Toward Water Wells
Project Type: Research
Start Date: 3/01/2011
End Date: 2/28/2012
Congressional District: 6th
Focus Categories: Groundwater, Solute Transport, Management and Planning
Keywords: Scavenger Well, Uncertainty, Chance Constraint, Model Averaging, Prediction, Saltwater Intrusion, Aquifer, Subsurface, Modeling, Optimization, Management
Principal Investigator: Tsai, Frank (Louisiana State University)
Federal Funds: $ 15,606
Non-Federal Matching Funds: $ 31,563
Abstract: The project goal is to design a scavenger well network to protect water wells in the “1,500-foot” sand aquifer in the Baton Rouge area, Louisiana under the consideration of model uncertainty. Scavenger wells are small extraction wells that pump out salty water before it reaches water wells. Model uncertainty contains model structure uncertainty and model parameter uncertainty. Due to lack of hydrogeological data, model structure uncertainty leads to non-unique conceptual ground water models. We often find a number of possible conceptual simulation models that explain the same hydrogeological processes. To cope with model uncertainty in the management problem, the objectives of the proposal are (1) to develop a multimodel approach using the Bayesian model averaging method to integrate multiple saltwater intrusion models for prediction and management of saltwater intrusion, and (2) to develop a chance-constrained approach to formulate stochastic remediation designs for risk/reliability analysis. Specifically, the project will consider multiple parameterization methods and variogram models for hydraulic conductivity estimation. The project will also consider the uncertainty in initial and boundary conditions to develop a number of saltwater simulation models. Moreover, the chance-constrained formulation is an important approach to study the overdesign issue is the risk-based probabilistic constraint formulation. The degree of overdesign is proportional to the reliability level of constraints that are not violated. The project will involve the Bayesian statistics into the chance-constrained formulation for a broader risk analysis. The project will adopt a Bayesian model averaging (BMA) method to address the uncertainty and non-uniqueness issues in saltwater intrusion management model. The BMA will integrate multiple saltwater intrusion models for prediction and management of saltwater intrusion under chance-constrained formulation. The project will implement the proposed methodology to the scavenger well network design to stop saltwater reaching the water wells in the "1,500-foot" sand aquifer of the Baton Rouge area.

Progress/Completion Report, 2011, PDF

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