HW #1 - Reproducible Time-Series Analysis, Temporal Scaling, and Visualizations

Overview

This repository contains a reproducible time-series analysis of daily USGS streamflow data from four Utah gaging stations. The project evaluates how temporal aggregation (daily, weekly, monthly) affects interpretation of snowmelt-driven hydrologic behavior.

Study period: Water Years 2015–2020 (Oct 2014 – Sept 2020).

This repository contains data of streamflow from:

• Lake Fork River at/above Moon Lake, UT (North of Duchesne, UT) USGS Site Number 09289500

• Green River near Jensen, UT (East of Vernal, UT) USGS Site Number 09261000

• Colorado River at Potash, UT (West of Moab, UT) USGS Site Number 09185600

• Colorado River near Cisco, UT (East of Moab, UT) USGS Site Number 09180500

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Repository Structure

reproducible-streamflow-analysis/

── data/

└── 09289500_1980_2020.csv

└── 09261000_1980_2020.csv

└── 09185600_1980_2020.csv

└── 09180500_1980_2020.csv

── notebooks/

└── Reproducible_Streamflow_Analysis.ipynb

── Py310_HW1.yml

── README.md

── .gitignore

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Environment Setup

Create the Conda environment:

On CHPC

module load miniconda3
conda env create -f Py310_HW1.yml
conda activate Py310_HW1

Local Machine

conda env create -f Py310_HW1.yml
conda activate Py310_HW1

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Required Packages

• Python 3.10
• pandas
• matplotlib
• ipykernel

All dependencies are specified in Py310_HW1.yml.

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Running the Analysis

1. Activate the environment:

conda activate Py310_HW1

2. Open:

notebooks/Reproducible_Streamflow_Analysis.ipynb

3. Select kernel:

Py310_HW1

4. Run all cells sequentially to reproduce figures and results.

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Author

Magnus Tveit
CVEEN 6920 – Hydroinformatics
University of Utah