ABSTRACT:

This resource contains a SQLite database of temperature values recorded at 15-minute intervals between 2014 and 2018 at the iUTAH GAMUT sites in the Logan River Watershed. Additionally contained with in this resource is a Jupyter Notebook that:

1) defines a function for querying the SQLite database and extracting the data for each site
2) gets temperature time series from database using function
3) creates time series for each year of data at each site
4) re samples the complete time series at each site to get the mean daily temperature
5) creates a figure showing (a) a plot of the mean daily temperature at each site between 2014 and 2018 and (b) a plot for each year of data showing a box plot of the temperature data recorded that year for each site.

ABSTRACT:

For environmental data measured by a variety of sensors and compiled from various sources, practitioners need tools that facilitate data access and data analysis. Data are often organized in formats that are incompatible with each other and that prevent full data integration. Furthermore, analyses of these data are hampered by the inadequate mechanisms for storage and organization. Ideally, data should be centrally housed and organized in an intuitive structure with established patterns for analyses. However, in reality, the data are often scattered in multiple files without uniform structure that must be transferred between users and called individually and manually for each analysis. This effort describes a process for compiling environmental data into a single, central database that can be accessed for analyses. We use the Logan River watershed and observed water level, discharge, specific conductance, and temperature as a test case. Of interest is analysis of flow partitioning. We formatted data files and organized them into a hierarchy, and we developed scripts that import the data to a database with structure designed for hydrologic time series data. Scripts access the populated database to determine baseflow separation, flow balance, and mass balance and visualize the results. The analyses were compiled into a package of scripts in Python, which can be modified and run by scientists and researchers to determine gains and losses in reaches of interest. To facilitate reproducibility, the database and associated scripts were shared to HydroShare as Jupyter Notebooks so that any user can access the data and perform the analyses, which facilitates standardization of these operations.

ABSTRACT:

This document provides an overview of the accompanying data files used in the production of the manuscript entitled "Application of flow and ion data to estimate ungaged inflows and losses in urban and agricultural sub-reaches of the Logan River Observatory".

Flow_Mass_Balance_Data.csv
Discharge and ion data for the mainstem sites, tributaries, and diversions used in the flow and mass balance analysis.

Chemistry_Data.csv
Sampling locations and measured ion concentrations of ungaged inflows used in the HCA analysis.

Daily_Stream_Flow.csv
Daily averaged discharge data for the gages used in the net flow balance of R1 and R2.

ABSTRACT:

This resources contains WSE and Discharge data for the Logan River Observatory Spawn Creek Gaging Station.

ABSTRACT:

This resource contains WSE and Discharge data for the Logan River Observatory gaging station on Temple Fork Creek below Sawmill Spring.

ABSTRACT:

This resource contains data files, scripts, results and figures used in the production of the manuscript entitled "Karst Hydrologic Memory Supplements Streamflow during Dry Periods in Snow-Dominated, Mountainous Watersheds".