My masters thesis involved work in three areas:
- Theory and representation of the benefit of environmental flows in a mathematical model
- Downscaling ecosystem information to the stream-reach scale in order to support estimation of environmental benefit
- Running an evolutionary algorithm to look at the tradeoff curves (Pareto front) of environment vs economic uses with the then-current draft natural flow regime data.
Read the thesis
The thesis itself can be found here: Estimating Tradeoffs in Environmental Flows with Evolutionary Algorithms – Full Thesis
Presentations
Two presentations on the thesis are below. The first is a short version given at a conference, the California Water and Environmental Modeling Forum’s 2020 meeting, and the long-version to Jay Lund’s lab group. Both audiences are familiar with California water issues and optimization algorithms (generally), so some details are skipped.
Slides for the long-version can be found here: Santos – Estimating Tradeoffs in Environmental Flows with Evolutionary Algorithms – Slides
Short presentation at CWEMF 2020.
Long version to Jay Lund’s lab group
Code
The software I wrote for this thesis can be found in two locations:
- https://github.com/ceff-tech/belleflopt has the optimization code
- https://github.com/ceff-tech/ProbabilisticPISCES has the code used to downscale PISCES species range data onto NHD stream segments