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Algorithm Development for Decision Support


Decision Support for the Sustainable Management of California Groundwater

groundwater

Motivation

Current models for groundwater resource estimation are relatively accurate but too complicated for decision support. The CA Sustainable Groundwater Management Act requires that groundwater be managed sustainably by local authorities.

Objective

Develop a prototype for decision support capability for groundwater resource management that allows fast what-if scenario analysis and enables timely decisions.

Proposed approach

Train computationally cheap surrogate models on available observation data at the watershed scale. This will enable decision makers to run many what-if scenarios in order to manage groundwater optimally.


Contact

For more information, contact Juliane Mueller

Related publications

J. Mueller, J. Park, R.Sahu, C. Varadharajan, B. Arora, B. Faybishenko, D. Agarwal, "An algorithmic framework for the optimization of computationally expensive bi-fidelity black-box problems", preprint., 2019. [link].