scholarly journals Discrete and continuous water-quality data and hydrologic parameters from seven agricultural watersheds in the United States, 2002-09

Data Series ◽  
10.3133/ds603 ◽  
2011 ◽  
Author(s):  
Kathleen A. McCarthy ◽  
David C. Lampe ◽  
Paul D. Capel
2018 ◽  
Vol 27 (3) ◽  
pp. 203 ◽  
Author(s):  
Ashley J. Rust ◽  
Terri S. Hogue ◽  
Samuel Saxe ◽  
John McCray

Wildfires are increasing in size and severity in forested landscapes across the Western United States. Not only do fires alter land surfaces, but they also affect the surface water quality in downstream systems. Previous studies of individual fires have observed an increase in various forms of nutrients, ions, sediments and metals in stream water for different post-fire time periods. In this research, data were compiled for over 24 000 fires across the western United States to evaluate post-fire water-quality response. The database included millions of water-quality data points downstream of these fires, and was synthesised along with geophysical data from each burned watershed. Data from 159 fires in 153 burned watersheds were used to identify common water-quality response during the first 5 years after a fire. Within this large dataset, a subset of seven fires was examined further to identify trends in water-quality response. Change-point analysis was used to identify moments in the post-fire water-quality data where significant shifts in analyte concentrations occurred. Evaluating individual fires revealed strong initial increases or decreases in concentrations, depending on the analyte, that are masked when averaged over 5 years. Evidence from this analysis shows significant increases in nutrient flux (different forms of nitrogen and phosphorus), major-ion flux and metal concentrations are the most common changes in stream water quality within the first 5 years after fire. Dissolved constituents of ions and metals tended to decrease in concentration 5 years after fire whereas particulate matter concentration continued to increase. Assembling this unique and extensive dataset provided the opportunity to determine the most common post-fire water-quality changes in the large and diverse Western USA. Results from this study could inform studies in other parts of the world, will help parameterise and validate post-fire water-quality models, and assist communities affected by wildfire to anticipate changes to their water quality.


2019 ◽  
Vol 31 (5) ◽  
pp. 492-506
Author(s):  
John Millar Carroll ◽  
Jordan Beck ◽  
Elizabeth W Boyer ◽  
Shipi Dhanorkar ◽  
Srishti Gupta

Abstract Access to clean water is a critical challenge and opportunity for community-level collaboration. People rely on local water sources, but awareness of water quality and participation in water management is often limited. Lack of community engagement can increase risks of water catastrophes, such as those in Flint, Michigan, and Cape Town, South Africa. We investigated water quality practices in a watershed system serving c.100 000 people in the United States. We identified a range of entities including government and nonprofit citizen groups that gather water quality data. Many of these data are accessible in principle to citizens. However, the data are scattered and diverse; information infrastructures are primitive and not integrated. Water quality data and data practices are hidden in plain sight. Based on fieldwork, we consider sociotechnical courses of action, drawing on best practices in human–computer interaction and community informatics, data and environmental systems management.


2017 ◽  
Vol 03 (04) ◽  
pp. 1750006 ◽  
Author(s):  
Travis Warziniack ◽  
Chi Ho Sham ◽  
Robert Morgan ◽  
Yasha Feferholtz

This paper studies the relationship between forest cover and drinking water chemical treatment costs using land use data and a survey by the American Water Works Association (AWWA). The survey gathers cost and water quality data from 37 treatment plants in forested ecoregions of the United States. We model the effect of forest conversion on the cost of water treatment using a two-step process. First, we examine the effect of changes in land use on water quality through an ecological production function. Second, we examine the effect of changes in water quality on cost of treatment through an economic benefits function. We find a negative relationship between forest cover and turbidity, but no relationship between forest cover and total organic carbon (TOC). Increasing forest cover in a watershed by 1% reduces turbidity by 3%, and increasing development by 1% in a watershed increases turbidity by 3%. The impact of development is more consistent across models than the impact of forest cover. We also find a large impact on turbidity from grazing in the watershed. Our economic benefits function shows a 1% increase in turbidity increases water treatment costs by 0.19%, and 1% increase in TOC increases water treatment costs by 0.46%. TOC has a clearer impact on costs than turbidity, which becomes insignificant when we omit one of our observations with high turbidity.


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