Graduation Date

Spring 2022

Document Type

Thesis

Program

Master of Science degree with a major in Environmental Systems, option Environmental Resources Engineering

Committee Chair Name

Dr. Eileen Cashman

Committee Chair Affiliation

HSU Faculty or Staff

Second Committee Member Name

Dr. Margaret Lang

Second Committee Member Affiliation

HSU Faculty or Staff

Third Committee Member Name

Dr. Brad Finney

Third Committee Member Affiliation

HSU Faculty or Staff

Subject Categories

Environmental Resources Engineering

Abstract

The demand for energy is increasing daily. Currently, non-renewable energy is used to meet much of the energy demand. Nonrenewable resources cause an increase in atmospheric carbon concentration and are a significant cause of climate change.

Governments throughout the world are supporting the use of renewable sources by providing financial and legislative support to reduce the carbon footprint in energy generation. In addition, having a variety of renewable energy sources in the portfolio would also complement each other, thereby providing a continuous supply of electricity to the people.

Redwood Coast Energy Authority is a local government Joint Powers Agency in Humboldt County, California. The agency supports an assessment of the potential for small-scale hydropower to facilitate the development of small hydroelectric projects in Northern California Watersheds for a more complete renewable energy portfolio.

Evaluating the appropriateness of developing a preliminary guideline for a small run-of-the-river hydropower production requires consideration of not only the river hydrology and topography but many other related criteria that will impact the project. This thesis will not address all critical components needed to decide whether to move forward with hydroelectric development but will focus on generating appropriate flow data using techniques like the drainage area ratio method (RAM), lumped modeling (L), semi-lumped modeling (SL), and distributed modeling.

The analysis showed reliable results for all the catchments considered under the case study with different potential generation outputs. Results also showed how each flow estimation method performed, and the results looked very similar to one another. In addition, the analysis also showed that the best time for power generation is between the months of November through March, and the sites have almost no power potential in the summer months, especially for the months of July through September. Overall, the results were very similar and showed similar trends where the models were unable to predict the very high flows that usually occur in December but were able to predict flows in the remaining time very well when compared with the observed data.

Citation Style

ASCE

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