ArticleThe Science of the total environment2020
Patterns and predictions of drinking water nitrate violations across the conterminous United States.
Article in The Science of the total environment, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Leveraging Artificial Intelligence in Allergy, Asthma, and Immunology With Environmental Exposures.Allergy · 2026Review
- The US EPA's National Nutrient Inventory: Critical Shifts in US Nutrient Pollution Sources from 1987 to 2017.Environmental science & technology · 2025Article
- Changes in meat consumption can improve groundwater quality.Nature food · 2025Article
- Estimates of Lake Nitrogen, Phosphorus, and Chlorophyll-Earth's future · 2024Article
- Vadose zone flushing of fertilizer tracked by isotopes of water and nitrate.Vadose zone journal : VZJ · 2024Article
- Predicting Redox Conditions in Groundwater at a National Scale Using Random Forest Classification.Environmental science & technology · 2024Article
- Prioritizing river basins for nutrient studies.Environmental monitoring and assessment · 2024Article
- Our national nutrient reduction needs: Applying a conservation prioritization framework to US agricultural lands.Journal of environmental management · 2024Article
- Nutrient Explorer: An analytical framework to visualize and investigate drivers of surface water quality.Environmental modelling & software : with environment data news · 2023Article
- An investigation of the seasonal relationships between meteorological factors, water quality, and sporadic cases of Legionnaires' disease in Washington, DC.Epidemiology and infection · 2023Article
- Predicting Potential Climate Change Impacts on Groundwater Nitrate Pollution and Risk in an Intensely Cultivated Area of South Asia.ACS environmental Au · 2022Article
- Deep soil nitrogen storage slows nitrate leaching through the vadose zone.Agriculture, ecosystems & environment · 2022Article
- Regional patterns and drivers of total nitrogen trends in the Chesapeake Bay watershed: Insights from machine learning approaches and management implications.Water research · 2022Article
- Examining Relationships Between Groundwater Nitrate Concentrations in Drinking Water and Landscape Characteristics to Understand Health Risks.GeoHealth · 2022Article
- Prediction of groundwater nitrate concentration in a semiarid region using hybrid Bayesian artificial intelligence approaches.Environmental science and pollution research international · 2022Article
- Wildfires can increase regulated nitrate, arsenic, and disinfection byproduct violations and concentrations in public drinking water supplies.The Science of the total environment · 2022Article
- Comparative health risk assessment of nitrate in drinking groundwater resources of urban and rural regions (Isfahan, Iran), using GIS.Environmental monitoring and assessment · 2021Article
- Nitrogen inputs best predict farm field nitrate leaching in the Willamette Valley, Oregon.Nutrient cycling in agroecosystems · 2021Article
- Coupling the dual isotopes of water (δEnvironmental research letters : ERL [Web site] · 2021Article
- Linking remote sensing with crop modeling for yield and nitrate leaching predictions in Minnesota.Journal of environmental qualityArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Excess nitrate in drinking water is a human health concern, especially for young children. Public drinking water systems in violation of the 10 mg nitrate-N/L maximum contaminant level (MCL) must be reported in EPA's Safe Drinking Water Information System (SDWIS). We used SDWIS data with random forest modeling to examine the drivers of nitrate violations across the conterminous U.S. and to predict where public water systems are at risk of exceeding the nitrate MCL. As explanatory variables, we used land cover, nitrogen inputs, soil/hydrogeology, and climate variables. While we looked at the role of nitrate treatment in separate analyses, we did not include treatment as a factor in the final models, due to incomplete information in SDWIS. For groundwater (GW) systems, a classification model correctly classified 79% of catchments in violation and a regression model explained 43% of the variation in nitrate concentrations above the MCL. The most important variables in the GW classification model were % cropland, agricultural drainage, irrigation-to-precipitation ratio, nitrogen surplus, and surplus precipitation. Regions predicted to have risk for nitrate violations in GW were the Central California Valley, parts of Washington, Idaho, the Great Plains, Piedmont of Pennsylvania and Coastal Plains of Delaware, and regions of Wisconsin, Iowa, and Minnesota. For surface water (SW) systems, a classification model correctly classified 90% of catchments and a regression model explained 52% of the variation in nitrate concentration. The variables most important for the SW classification model were largely hydroclimatic variables including surplus precipitation, irrigation-to-precipitation ratio, and % shrubland. Areas at greatest risk for SW nitrate violations were generally in the non-mountainous west and southwest. Identifying the areas with possible risk for future violations and potential drivers of nitrate violations across U.S. can inform decisions on how source water protection and other management options could best protect drinking water.
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