Supplementary Files for: Quantifying the Impact of Rain-On-Snow Induced Flooding in the Western United States

Creators

Emma Watts, Utah State UniversityFollow
Brennan Bean, Utah State UniversityFollow

Description

Serious flooding can happen when rain falls on snow, which we call a rain-on-snow (ROS) event. Increasing our understanding of the behavior of floods resulting from ROS events can help us design better systems to manage flood water and prevent it from causing damage. This thesis explores how ROS events affect streamflow in the Western United States by examining the weather conditions that precede a streamflow surge. We classify stream surges as ROS or non-ROS induced based on these weather conditions, which helps us separate floods caused by ROS events from those caused by other factors. By comparing these different types of floods, we find that ROS induced floods are generally 3-20\% larger than other floods. Engineers can use these findings and data to conservatively adjust drainage system designs, like culverts, to better handle the increased water flow during ROS events. This will reduce potential damage and make our road and building structures better able to handle extreme flooding.

Author ORCID Identifier

Brennan Bean https://orcid.org/0000-0002-2853-0455

Document Type

Dataset

DCMI Type

Dataset

File Format

.R, .Rproj, .csv

Publication Date

9-5-2024

Publisher

Utah State University

Methodology

This repository contains the data and code necessary to reproduce the figures and results in the above-referenced MS Thesis. The main product is peak_data_sf_FIXED.csv (use read.csv2() to read into R). It also includes the following folders (listed in alphabetical order):

data-raw: This folder contains all the formatted data sources necessary to recreate final figures and results in the repository. These data sources are derived from publicly available snow, weather, and water data available from several federal sources cited in the thesis and referenced in the scripts folder. - modeling: All datasets used in the modeling process, for both the GAMs and ML application - peaks: Streamflow peak data, including corresponding calculated baseflows - rhv_tot/fhv_miss: Cleaned streamflow data prior to peak detection, rhv_tot containing data downloaded successfully on the first attempt and rhv_miss containing data obtained for streamgages that failed to download initially - ros_class: Streamflow peaks with accompanying ROS vs non ROS classification - snotel: Snowpack telemetry station data, used to determine weather conditions preceding a storm surge. - usgs_fs: Streamgage identifier and flood stage data - wbd: Watershed boundary dataset

figures: This folder contains copies of all thesis figures along with the R code necessary to reproduce them. R code is organized by chapter and scripts are named corresponding to figure numbers as they appear in the thesis. Note: a Google API key needs to be obtained and imported in order to run the code in fig2_11.R, which includes an overlay over a background map.

R: This folder contains copies of functions necessary to download the raw data sources. Two of these functions come directly from the rsnodas package (see https://github.com/lschneider93/rsnodas)

scripts: This folder contains the R code required to reproduce the data workflows described in this thesis. Script name includes the order in which the scripts should be run. Note that scripts 1-8 all contribute to the creation of the final dataset. These scripts require long data download steps and their reproducibility are conditional upon current server availability as of 8/24/2024 for all publicly available datasets.

Language

eng

Code Lists

see README

Disciplines

Applied Statistics | Statistics and Probability

License

This work is licensed under a Creative Commons Attribution 4.0 License.

Recommended Citation

Watts, Emma and Bean, Brennan, "Supplementary Files for: Quantifying the Impact of Rain-On-Snow Induced Flooding in the Western United States" (2024). Browse all Datasets. Paper 235.
https://digitalcommons.usu.edu/all_datasets/235