ABSTRACT:

This note is created to help calculate the infiltration rate of soil using the Green-Ampt infiltration model.

ABSTRACT:

Ammonia exhaust tailpipe mixing ratios (ppm) from 47 light-duty gasoline motor vehicles were quantified using a portable ECM miniPEMS over on-road Real Driving Emissions (RDE) tests. The ECM miniPEMS was also used to retrieve various parameters data from the vehicle’s OBDII port such as vehicle speed, the revolution per minute (RPM) readings, engine load percentages, air-fuel ratio, and the temperature of the three-way catalyst converters. The vehicle exhaust temperature was also measured by the ECM miniPEMS using Type K thermocouples. The RDE tests were conducted on a 5.3-mile predefined urban testing route designed using the local road network in the City of Logan, Utah. The urban testing route included residential and highway roads, uphill and downhill road segments, stop signs, traffic lights, and a school zone with a reduced speed limit. The test cycle was coded as UWRL-UDTC (The Utah Water Research Laboratory Urban Driving Test Cycle). The portable Applus Autologic 5-Gas Portable Vehicle Gas Analyzer (model 310-0220) was also used to measure tailpipe mixing ratios (ppm) of post-catalyst carbon monoxide. Both instruments were carried onboard the tested vehicles during the test, while their sensors were mounted in the tested vehicle’s engine exhaust. The vehicle test sample of 47 light-duty gasoline motor vehicles was chosen to represent the same tier-level distribution as the on-road gasoline vehicle fleet along the Wasatch Front and the Cache County located in the U.S. State of Utah. Vehicle specifications including type, make, model, model year, mileage reading, engine displacement, number of cylinders, gross vehicle weight rating (GVWR), and tailpipe diameter were also collected for all tested vehicles. Atmospheric temperature and pressure at the time of testing were also measured. All the data collected throughout the project are included in the "Content" section of this resource. The "Content" section also includes an R Jupyter notebook used to analyze collected data. The mixing ratios of exhaust gases were first converted into emission rates (mg per mile), then, many descriptive and inferential statistical analyses and correlation analyses were performed. Many plots were also generated using the R script included in the Jupyter notebook. The main outcomes of this study can be found in the article included in the "Related Resources" section of this resource.

ABSTRACT:

The purpose of this resource is to automate extraction of discharge data from the United States Geological Survey (USGS) National Water Information System (NWIS) (https://waterdata.usgs.gov/nwis), precipitation from PRISM Climate Group database (https://prism.oregonstate.edu/), and evapotranspiration from the OpenET databases (https://openetdata.org/). This resource is part of a semester project for the USU CEE 6110: Hydroinformatics class (Spring 2022).

ABSTRACT:

Existing models fail to represent future drought-like hydrologic inflow conditions in the Upper Colorado River Basin (UCRB) based on intensifying basin aridification. Hence, this study uses the Colorado River Simulation System (CRSS) model to investigate the effects of intensifying drought and changes in conservation and consumption of the UCRB on Lake Powell storage. The study also investigated the impact of linking Lake Powell’s outflow to UCRB’s hydrology using a new rule. The intensifying drought-like conditions in the URCB were simulated using the natural inflow data taken during the (2000 - 2018) drought period. The data was decreased by 20%, 35%, and 50%, respectively, portraying future intensifying drought responses to climate change. Changes in demand scenarios were simulated by changing the amounts of flow diverted from Lake Powell (increased consumption) and to Lake Powell (increased conservation). Model results were also utilized to predict the amount of time until Lake Powell storage levels reach the power pool elevation of 3490 feet. The results clearly show that under the 2016 Upper and Lower Basins Demands, the intensifying drought would greatly decrease Lake Powell storage and shorten the time until storage levels drop below the power pool elevation of 3490 feet. Additionally, having the outflow linked to the basin’s hydrology would save storage from reaching alarming levels. Saving some water as low as 5 % would stabilize the elevation. The CRSS outcomes also showed that increasing consumption in the UCRB would reduce the amount of storage in Lake Powell, whereas increasing conservation would increase the storage of Lake Powell.

See readme file for instructions on how to use this resource.

ABSTRACT:

The purpose of this HydroShare resource is to facilitate the extraction of monthly-averaged Evapotranspiration (ET) data from the OpenET database (https://openetdata.org/). This resource could be used to extract ET data at one point using its latitude & longitude. The resource could also be used to have an average ET value at the watershed scale using a shapefile of the watershed of interest.
The OpenET uses the best available science to provide easily accessible satellite-based estimates of evapotranspiration (ET) (https://openetdata.org/about/). The OpenET database provides ET data using the Ensemble method.

ABSTRACT:

Example of running the The Regional Hydro-Ecological Simulation System (RHESSys)

ABSTRACT:

This Jupyter Notebook and associated python file illustrates the use of the ModelMyWaterShed API for watershed delineation from an arbitrary point on or near NHD Plus streams in the U.S. This is documented at https://modelmywatershed.org/api/docs/.

ABSTRACT:

Existing models fail to represent future drought-like hydrologic inflow conditions in the Upper Colorado River Basin (UCRB) based on intensifying basin aridification. Hence, this study uses the Colorado River Simulation System (CRSS) model to investigate the effects of intensifying drought and changes in conservation and consumption of the UCRB on Lake Powell storage. The study also investigated the impact of linking Lake Powell’s outflow to UCRB’s hydrology using a new rule. The intensifying drought-like conditions in the URCB were simulated using the natural inflow data taken during the (2000 - 2018) drought period. The data was decreased by 20%, 35%, and 50%, respectively, portraying future intensifying drought responses to climate change. Changes in demand scenarios were simulated by changing the amounts of flow diverted from Lake Powell (increased consumption) and to Lake Powell (increased conservation). Model results were also utilized to predict the amount of time until Lake Powell storage levels reach the power pool elevation of 3490 feet. The results clearly show that under the 2016 Upper and Lower Basins Demands, the intensifying drought would greatly decrease Lake Powell storage and shorten the time until storage levels drop below the power pool elevation of 3490 feet. Additionally, having the outflow linked to the basin’s hydrology would save storage from reaching alarming levels. Saving some water as low as 5 % would stabilize the elevation. The CRSS outcomes also showed that increasing consumption in the UCRB would reduce the amount of storage in Lake Powell, whereas increasing conservation would increase the storage of Lake Powell.

See readme file for instructions on how to use this resource.

ABSTRACT:

This project aims to use remote sensing data from the Landsata database from Google Earth Engine to evaluate the spatial extent changes in the Bear Lake located between the US states of Utah and Idaho. This work is part of a term project submitted to Dr Alfonso Torres-Rua as a requirment to pass the Remote Sensing of Land Surfaces class (CEE6003). More information about the course is provided below. This project uses the geemap Python package (https://github.com/giswqs/geemap) for dealing with the google earth engine datasets. The content of this notebook can be used to:

learn how to retrive the Landsat 8 remote sensed data. The same functions and methodology can also be used to get the data of other Landsat satallites and other satallites such as Sentinel-2, Sentinel-3 and many others. However, slight changes might be required when dealing with other satallites then Landsat.
Learn how to create time lapse images that visulaize changes in some parameters over time.
Learn how to use supervised classification to track the changes in the spatial extent of water bodies such as Bear Lake that is located between the US states of Utah and Idaho.
Learn how to use different functions and tools that are part of the geemap Python package. More information about the geemap Pyhton package can be found at https://github.com/giswqs/geemap and https://github.com/diviningwater/RS_of_Land_Surfaces_laboratory
Course information:

Name: Remote Sensing of Land Surfaces class (CEE6003)
Instructor: Alfonso Torres-Rua (alfonso.torres@usu.edu)
School: Utah State University
Semester: Spring semester 2023