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:

Climate and environmental uncertainties are driving many communities to adopt water conservation strategies related to agricultural water use and irrigation efficiency. While water managers are equipped to understand the technical aspects of improved irrigation efficiencies(e.g. application rate), there are few tools to represent how a water balance responds to changes in management practices. This study seeks to understand the extent to which irrigation excess serves as recharge to streamflow and how this relationship varies with different irrigation practices. We developed a model to predict infiltration and runoff (surrogate for recharge)as a function of applied irrigation,precipitation, evapotranspiration, and soil type. This model was applied to a section of the lower Logan River between Main Street and Mendon Road, which is notably impacted by agricultural operations during the summer growing period. We used this model to evaluate the extent to which irrigation recharge supplements flow at Mendon Road and also evaluated the impact of irrigation timing and irrigation efficiency on recharge. Our model showed that observed flow at Mendon Road had a similar trend and magnitude to modeled recharge during low flow conditions.In addition, we found that irrigation timing had little impact on recharge while reducing the rate of irrigation application by 40% corresponded to a 75% reduction in recharge during summer months. On a broader scale, the results of this case study demonstrate the importance of considering “the paradox of irrigation efficiency” in water resource decision making.

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".

ABSTRACT:

This resource provides the data, models, model results, scripts, and figures for the manuscript "Quantifying Dynamic River Gains and Losses Using Inverse Water Temperature Modeling".

ABSTRACT:

The Measurement and Infrastructure Gap Analysis in Utah's Sevier River Basin consisted of a comprehensive inventory and evaluation of existing diversion and stream measurement infrastructure along 30 subsystems with 4 distribution systems: the Upper Sevier River, Lower Sevier River, Upper San Pitch River, Lower San Pitch River. The primary objective of this “Gap Analysis” was to develop methods to identify and rank areas throughout the Sevier River Basin where new or updated measurement infrastructure is needed to serve water rights holders. A ranking analysis combined existing measurement infrastructure gaps and potential spatial gaps to create a ranked list of potential new and updates to current measurement infrastructure. Stakeholder feedback was solicited and used to create a stakeholder identified needs list.

In total, we documented 147 existing measurement stations in the Sever River basin along selected subsystems. This included 88 diversion and 59 streamgaging stations. Of these 147 existing stations, 34 diversion stations and 16 streamgages were found to be in need of updates to the existing infrastructure. Stations in need of measurement infrastructure updates were concentrated in the Upper San Pitch distribution system.

Stakeholders identified 73 proposed locations for new stations and 55 existing stations in need of infrastructure updates. The majority of requests were concentrated in the Upper Sevier distribution system, which accounted for 53 proposed new stations and 17 requests for updates to existing infrastructure. The Lower Sevier distribution system had 5 requests for new stations and 10 requests for infrastructure updates. In the Upper San Pitch distribution system, stakeholders identified 7 potential new station locations and 19 existing stations requiring updates, while the Lower San Pitch distribution system had 8 requests for new stations and 9 requests for updates to existing infrastructure.

In addition to the stakeholder identified needs for new stations and updates to existing, USU completed an independent analysis of where future investment should be targeted. For example, the analysis identified gaging the San Pitch at its confluence with the Sevier River as critical to accounting in the basin, as well as making updates to stations on the mainstem of the San Pitch to better account for gains and losses as water moves through the system. These findings reflected the priorities identified by water rights holders and by state WRi engineers.