Risk-Based Wellhead Protection Decision Support: A Repeatable Workflow Approach

Area of Science:

• Environmental science
• Hydrogeology
• Water resource management

Background:

• Environmental water management benefits from risk-based approaches incorporating uncertainty.
• Data assimilation and model construction are complex, time-consuming, and error-prone processes.
• A repeatable workflow is crucial for efficient and rigorous analysis of environmental data.

Purpose of the Study:

• To develop a scripted workflow for groundwater model construction, data assimilation, and probabilistic source water delineation.
• To address the need for a repeatable and transparent approach in environmental risk assessment.
• To create a decision tool for water managers to delineate risk-based capture zones for supply wells.

Main Methods:

• Leveraged existing datasets on hydrogeology, hydrography, water use, and recharge.
• Developed a scripted workflow for groundwater model construction and data assimilation.
• Employed ensemble-based history matching and a posterior Monte Carlo approach for probabilistic capture zone delineation.

Main Results:

• Generated a repeatable workflow for groundwater model construction and data assimilation.
• Provided probabilistic capture zones for source water to wells within a risk-based framework.
• The workflow is applicable to United States datasets and similar global datasets.

Conclusions:

• The developed workflow offers a repeatable, transparent, and efficient method for risk-based environmental water management.
• Open-source tools facilitate the testing and application of this approach for various environmental problems.
• Water managers can utilize probabilistic capture zones to inform decisions on source water protection based on risk tolerance.