Using a cloud to replenish parched groundwater modeling efforts

Area of Science:

• Environmental science
• Hydrogeology
• Computational modeling

Background:

• Groundwater models benefit from increased parameter flexibility and soft-knowledge integration.
• These advanced methods require significant computational resources, posing a barrier to widespread adoption.
• Traditional computing infrastructure limits the scope and frequency of complex groundwater modeling tasks.

Purpose of the Study:

• To explore the application of cloud computing for enhancing groundwater model calibration and uncertainty analysis.
• To demonstrate how cloud-based resources can overcome computational limitations in sophisticated groundwater modeling.

Main Methods:

• Utilizing cloud computing platforms to access scalable and on-demand virtual computing power.
• Implementing techniques for creating, launching, and terminating virtual machines as needed.
• Leveraging cloud storage for saving and reusing machine images for future modeling sessions.

Main Results:

• Cloud computing provides cost-effective and flexible access to high-performance computing for groundwater modelers.
• The use of virtual computers allows for routine execution of complex model calibration and uncertainty analyses.
• Enables advanced modeling approaches that were previously computationally prohibitive.

Conclusions:

• Cloud computing democratizes access to advanced computational resources for hydrogeological studies.
• Modelers can now perform sophisticated groundwater model calibration and uncertainty analysis more efficiently and routinely.
• This technological shift empowers more robust and comprehensive groundwater resource management and research.