Geology topics

Brioch Hemmings

Publications and source records attributed to Brioch Hemmings.

3 recordsLinked to original sources

USGS2024

Self-guided decision support groundwater modelling with Python

The GMDSI tutorial notebooks repository provides learners with a comprehensive set of tutorials for self-guided training on decision-support groundwater modelling using Python-based tools. Although targeted at groundwater modelling, they are based around model-agnostic tools and readily transferable to other environmental modelling workflows. The tutorials are divided into three parts. The first covers fundamental theoretical concepts. These are intended as background reading for reference on an as-needed basis. Tutorials in the second part introduce learners to some of the core concepts parameter estimation in a groundwater modelling context, as well as providing a gentle introduction to the PEST, PEST++ and pyEMU software. Lastly, the third part demonstrates how to implement highly-parameterized applied decision-support modelling workflows. The tutorials aim to provide examples of both “how to use” the software as well as “how to think” about using the software. A key advantage to using notebooks in this context is that the workflows described run the same code as practitioners would run on a large-scale real- world application. Using a small synthetic model facilitates rapid progression through the workflow.

Journal of Open Source Education↗

USGS2021

Towards improved environmental modeling outcomes: Enabling low-cost access to high-dimensional, geostatistical-based decision-support analyses

Computer models of environmental systems routinely inform decision making for water resource management. In this context, quantifying uncertainty in the important simulated outputs, and reducing uncertainty through assimilating historic system-state observations, is as important as the numerical model. However, implementing high-dimensional and stochastic workflows are challenging, often requiring that practitioners have theoretical and practical understanding of several advanced topics. Worse, implementing these important analyses can take substantial time and effort. This additional effort is often cited as justification for postponing, or even forgoing, these analyses. Herein, we present scripting tools to facilitate the efficient and repeatable construction of high-dimensional, geostatistical-based PEST interfaces, including uncertainty analyses. As demonstrated, these tools can be applied with minimal effort to a model with varied temporal and spatial discretization. Ultimately, these tools can enable low-cost access to valuable decision-support analyses earlier and more frequently during the modeling workflow.

Environmental Modelling & Software↗

USGS2020

Towards reproducible environmental modeling for decision support: A worked example

A fully worked example of decision-support-scale uncertainty quantification (UQ) and parameter estimation (PE) is presented. The analyses are implemented for an existing groundwater flow model of the Edwards aquifer, Texas, USA, and are completed in a script-based workflow that strives to be transparent and reproducible. High-dimensional PE is used to history-match simulated outputs to corresponding state observations of spring flow and groundwater level. Then a hindcast of a historical drought is made. Using available state observations recorded during drought conditions, the combined UQ and PE analyses are shown to yield an ensemble of model results that bracket the observed hydrologic responses. All files and scripts used for the analyses are placed in the public domain to serve as a template for other practitioners who are interested in undertaking these types of analyses.

Texas↗