The dataset includes field measurements and laboratory analysis of water-quality data collected by trained community technicians across the Yukon River Basin in Alaska and Canada and Yukon River Inter-Tribal Watershed Council staff and analyzed at the U.S. Geological Survey National Research Program laboratories in Boulder, CO.

The dataset includes field measurements and laboratory analysis of water-quality data collected by trained community technicians across the Yukon River Basin in Alaska and Canada and Yukon River Inter-Tribal Watershed Council staff and analyzed at the U.S. Geological Survey National Research Program laboratories in Boulder, CO.

The dataset includes field measurements and laboratory analysis of water-quality data collected by trained community technicians across the Yukon River Basin in Alaska and Canada and Yukon River Inter-Tribal Watershed Council staff and analyzed at the U.S. Geological Survey National Research Program laboratories in Boulder, CO.

This data repository documents the input files, output files, and RStudio scripts used to quantify changes in water-quality concentrations after the 2020 Cameron Peak Fire in the North Fork Big Thompson River and Buckhorn Creek watersheds using the Weighted Regressions on Time, Discharge, and Season (WRTDS) method. A WRTDS model was developed using 12 years of pre-fire data (2008-August 13, 2020) and used to make predictions of what water-quality concentrations could have been on post-fire (August 13, 2020-2023) sample days had there not been a fire. This method may be a useful tool for post-fire water-quality assessments in the western United States.

This dataset includes water temperature and water salinity data from continuous hydrology loggers and spot checks from a handheld water quality meter at restoration and reference sites at Willapa National Wildlife Refuge, from March 2014 to August 2015.

The data were collected summer, 2016, 2017, and 2018. Continuous temperature loggers were deployed along the Pend Oreille River between Albeni Falls Dam and the Box Canyon Dam. Loggers were checked every 1-2 weeks throughout the summer.

The data set contains temporal chloride concentrations (mg/L) and specific conductance (uS/cm) values for 32 wetlands and groundwater monitoring wells as well as the date(s) sampled and the laboratory where the water quality analyses were conducted. The ratio of chloride concentration to specific conductance is referred to as the Contamination Index. In this region, values greater than 0.035 are used to identify water quality samples that are contaminated with co-produced water from energy development.

The data set contains temporal chloride concentrations (mg/L) and specific conductance (uS/cm) values for 32 wetlands and groundwater monitoring wells as well as the date(s) sampled and the laboratory where the water quality analyses were conducted. The ratio of chloride concentration to specific conductance is referred to as the Contamination Index. In this region, values greater than 0.035 are used to identify water quality samples that are contaminated with co-produced water from energy development.

This section of the data release supports an archive of the models used in the associated publication. The U.S. Geological Survey and the University of Wisconsin – Green Bay collected hydrologic and water-quality data to assess the effectiveness of agricultural conservation management practice (CMP) implementation at Mainstem Plum Creek and West Plum Creek in northeastern Wisconsin. Monitoring data from 2010–2020 at Mainstem Plum and 2013–2020 at West Plum were used to detect changes in hydrologic and water-quality responses during runoff events. Runoff events were defined by hydrographers and used to compute event loads and event flow-weighted mean concentrations of total phosphorus and total suspended solids – all of which are included in the associated data release. Additionally, changes in these parameters were assessed between two time periods (“initial” and “post-CMP implementation”) using the models included in this model archive. Because event discharges, loads, and concentrations are influenced by factors such as weather and the conditions preceding events, random-forest and regression models were developed to control for these factors and to elucidate water-quality changes more directly associated with CMP implementation. Residuals from random-forest models were used to detect changes between the two time periods via Wilcoxon signed-rank tests, and multiple linear regression models were used to determine percent change in responses via time-period dummy variable coefficients. Results indicate statistically insignificant changes in most responses during runoff events.