Quantifying the role of large floods in riverine nutrient loadings using linear regression and analysis of covariance

Siddhartha Verma, Alena Bartosova, Momcilo Markus, Richard Cooke, Myoung Jin Um, Daeryong Park

Research output: Contribution to journalArticle

Abstract

This study analyzes the role of large river flow events in annual loads, for three constituents and for up to 32 years of daily data at multiple watersheds with different land-uses. Prior studies were mainly based on simple descriptive statistics, such as the percentage of nutrient loadings transported during several of the largest river flows, while this study uses log-regression and analysis of covariance (ANCOVA) to describe and quantify the relationships between large flow events and nutrient loadings. Regression relationships were developed to predict total annual loads based on loads exported by the largest events in a year for nitrate plus nitrite nitrogen (NO3-N + NO2-N, indicated as total oxidized nitrogen; TON), total phosphorus (TP), and suspended solids (SS) for eight watersheds in the Lake Erie and Ohio River basins. The median prediction errors for annual TON, TP, and SS loads from the top five load events for spatially aggregated watersheds were 13.2%, 18.6%, and 13.4%, respectively, which improve further on refining the spatial scales. ANCOVA suggests that the relationships between annual loads and large load events are regionally consistent. The findings outline the dominant role of large hydroclimatic events, and can help to improve the design of pollutant monitoring and agricultural conservation programs.

Original languageEnglish (US)
Article number2876
JournalSustainability (Switzerland)
Volume10
Issue number8
DOIs
StatePublished - Aug 13 2018

Keywords

  • ANCOVA
  • Annual load
  • Lake Erie
  • Log-regression
  • Ohio River
  • Suspended solids
  • Total oxidized nitrogen
  • Total phosphorus

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Renewable Energy, Sustainability and the Environment
  • Management, Monitoring, Policy and Law

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