Portfolio

Environmental Justice For Prisons

Geospatial Analysis, NASA Grant Project

At the Geospatial Centroid, I worked alongside Caitlin Mothes to choose and process open source datasets and calculate percentile scores in three separate categories: climate, effects, and exposure.

Each prison was then assigned a vulnerability score which combined all risk factors. This project taught me about managing a repository and working with large data.

Map data © OpenStreetMap contributors | OpenFreeMap © OpenMapTiles Data from OpenStreetMap
Low RiskHigh Risk

Cuyama Valley Groundwater Basin (2023 - 2025)

Groundwater Sustainability, Cartography

Served as the geospatial technician, water resource model support, and project data manager for all tasks for the reports.

Geospatial: developed layout template, basemap, and new figures for the Cuyama 2024 Annual Report (AR), 2025 Groundwater Sustainability Plan (GSP), and Groundwater Conditions reports using ArcGIS Pro and QGIS. To see my work, open the 2025 GSP document and look in the lower left corner for "dhunt".

Modeling: Utilized python and QGIS to incorporate yearly land use, ET, and other water usage parameters to the IWFM model, CBWRM.

Map data © OpenStreetMap contributors | OpenFreeMap © OpenMapTiles Data from OpenStreetMap

Yuba Subbasins Recharge Analysis (2023)

Groundwater Management, Spatial Analysis

Computed Recharge Suitability Index (RSI) scores using open-source geospatial data for the Yuba Subbasins. This analysis identified optimal locations for groundwater recharge projects.

By combining soil permeability data, slope analysis, land use classifications, and proximity to water sources, I created a comprehensive index score and suite of figures that guides decision-making for water management authorities.

Yuba Water. (2023b, December). Recharge Suitability Index: Development and Results.

Map data © OpenStreetMap contributors | OpenFreeMap © OpenMapTiles Data from OpenStreetMap

Urban Water Use Objective Reporting (circa 2024)

Groundwater Management, Large-data Analysis

Programmed a script to calculate Seasonal populations from Advanced Metering Infrastructure (AMI) data. This analysis helped clients comply with California requirements for Urban Water Use Objectives (UWUO).

R-language script wrangled, cleand, and processed >8 million records from 21,000 households. Algorithms within script adhered to Methods for Estimating Seasonal Populations with Water and Energy Data (DWR, 2022).

Map data © OpenStreetMap contributors | OpenFreeMap © OpenMapTiles Data from OpenStreetMap