ABSTRACT:

This resource provides data and code supporting the thesis “Irrigation Management and Soils as Controls on Deep Percolation and Nitrate Leaching in Agricultural Systems”. All data were collected from irrigated fields of cooperating producers between 2023 and 2025, and all code uses R statistical software. The ‘Chp 2: Methods Assessment’ section contains data and analysis focused on understanding soil water sensor and suction lysimeter behavior. Performance of two soil water sensors (HOBO Decagon 10HS, METER T12) were compared. Lysimeter sampling success, sample size, and volume of influence were assessed, and comparisons between soil water nitrate collected by lysimeters and converted from bulk soil nitrate were compared. ‘Chp 3: Percolation Metric’ contains code for calculating a volumetric water content response metric normalized to net water inputs for single irrigation events. Compiled metric scores across soil types are provided as well. ‘Chp 4: Fairfield Data and Time Variable Dual Permeability Modeling’ contains field data from soil water sensors, suction lysimeters, and soil samples collected in Fairfield during 2023 and 2024. It also contains R code that interfaces with Hydrus 1D to solve inverse model solutions for dual permeability model parameters, then running many executions of time-variable forward models to estimate deep percolation and nitrate leaching. ‘Chp 5: Gallatin Data and Single Porosity Models’ contains all field data from soil water sensors, suction lysimeters, and soil samples collected in the Gallatin during 2023 and 2024. It also contains code for running Hydrus 1D single porosity models calibrated to field site data.

ABSTRACT:

This resource contains data collected by the Whitefish Lake Institute (WLI) as well as R code used to compile and conduct quality assurance on the data. This resource reflects joint publication efforts between WLI and the Montana State University Extension Water Quality (MSUEWQ) program. All data included here was uploaded to the National Water Quality Portal (WQX) in 2022. It is the intention of WLI to upload all future data to WQX and this HydroShare resource may also be updated in the future with data for 2022 and forward.

Data Purpose:
The ‘Data’ folder of this resource holds the final data products for the extensive dataset collected by WLI between 2007 and 2021. This folder is likely of interest to users who want data for research and analysis purposes. This dataset contains physical water parameter field data collected by Hydrolab MS5 and DS5 loggers, including water temperature, specific conductance, dissolved oxygen concentration and saturation, barometric pressure, and turbidity. Additional field data that needs further quality assurance prior to use includes chlorophyll a, ORP, pH, and PAR. This dataset also contains water chemistry data analyzed at certified laboratories including total nitrogen, total phosphorus, nitrate, orthophosphate, total suspended solids, organic carbon, and chlorophyll a. The data folder includes R scripts with code for examples of data visualization. This dataset can provide insight to water quality trends in lakes and streams of northwestern Montana over time.
Data Summary:
During the time-period, WLI collected water quality data for 63 lake sites and 17 stream and river sites in northwestern Montana under two separate monitoring projects. The Northwest Montana Lakes Network (NMLN) project currently visits 41 lake sites in Northwestern Montana once per summer. Field data from Hydrolabs are collected at discrete depths throughout a lake's profile, and depth integrated water chemistry samples are collected as well. The Whitefish Water Quality Monitoring Project (WWQMP) currently visits two sites on Whitefish Lake, one site on Tally Lake, and 11 stream and river sites in the Whitefish Lake and Upper Whitefish River watersheds monthly between April and November. Field data is collected at one depth for streams and many depths throughout the lake profiles, and water chemistry samples are collected at discrete depths for Whitefish Lake and streams. The final dataset for both programs includes over 112,000 datapoints of data passing quality assurance assessment and an additional 72,000 datapoints that would need further quality assurance before use.

Workflow Purpose:
The ‘Workflow’ folder of this resource contains the raw data, folder structure, and R code used during this data compilation and upload process. This folder is likely of interest to users who have similar datasets and are interested in code for automating data compilation or upload processes. The R scripts included here have code to stitch together many individual Hydrolab MS5 and DS5 logger files as well as lab electronic data deliverables (EDDs), which may be useful for users who are interested in compiling one or multiple seasons' worth of data into a single file. Reformatting scripts format data to match the multi-sheet excel workbook format required by the Montana Department of Environmental Quality for uploads to WQX, and may be useful to others hoping to automate database uploads.
Workflow Summary:
Compilation code in the workflow folder compiles data from its most original forms, including Hydrolab sonde export files and lab EDDs. This compilation process includes extracting dates and times from comment fields and producing a single file from many input files. Formatting code then reformats the data to match WQX upload requirements, which includes generating unique activity IDs for data collected at the same site, date, and time then linking these activity IDs with results across worksheets in an excel workbook. Code for generating all quality assurance figures used in the decision-making process outlined in the Quality Assurance Document and resulting data removal decisions are included here as well. Finally, this folder includes code for combining data from the separate program uploads for WQX to the more user-friendly structure for analysis provided in the 'Data' file for this HydroShare resource.