Literature DB >> 29524667

Composite measures of watershed health from a water quality perspective.

Ganeshchandra Mallya1, Mohamed Hantush2, Rao S Govindaraju3.   

Abstract

Water quality data at gaging stations are typically compared with established federal, state, or local water quality standards to determine if violations (concentrations of specific constituents falling outside acceptable limits) have occurred. Based on the frequency and severity of water quality violations, risk metrics such as reliability, resilience, and vulnerability (R-R-V) are computed for assessing water quality-based watershed health. In this study, a modified methodology for computing R-R-V measures is presented, and a new composite watershed health index is proposed. Risk-based assessments for different water quality parameters are carried out using identified national sampling stations within the Upper Mississippi River Basin, the Maumee River Basin, and the Ohio River Basin. The distributional properties of risk measures with respect to water quality parameters are reported. Scaling behaviors of risk measures using stream order, specifically for the watershed health (WH) index, suggest that WH values increased with stream order for suspended sediment concentration, nitrogen, and orthophosphate in the Upper Mississippi River Basin. Spatial distribution of risk measures enable identification of locations exhibiting poor watershed health with respect to the chosen numerical standard, and the role of land use characteristics within the watershed.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Reliability; Resilience; Scaling; Stream networks; Trend analysis; Vulnerability; Water quality; Watershed health

Mesh:

Year:  2018        PMID: 29524667      PMCID: PMC7430237          DOI: 10.1016/j.jenvman.2018.02.049

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  5 in total

1.  Watershed reliability, resilience and vulnerability analysis under uncertainty using water quality data.

Authors:  Yamen M Hoque; Shivam Tripathi; Mohamed M Hantush; Rao S Govindaraju
Journal:  J Environ Manage       Date:  2012-06-12       Impact factor: 6.789

2.  Land use, spatial scale, and stream systems: lessons from an agricultural region.

Authors:  Bruce Vondracek; Kristen L Blann; Carson B Cox; Julia Frost Nerbonne; Karen G Mumford; Brian A Nerbonne; Laurie A Sovell; Julie K H Zimmerman
Journal:  Environ Manage       Date:  2005-12       Impact factor: 3.266

3.  Record-setting algal bloom in Lake Erie caused by agricultural and meteorological trends consistent with expected future conditions.

Authors:  Anna M Michalak; Eric J Anderson; Dmitry Beletsky; Steven Boland; Nathan S Bosch; Thomas B Bridgeman; Justin D Chaffin; Kyunghwa Cho; Rem Confesor; Irem Daloglu; Joseph V Depinto; Mary Anne Evans; Gary L Fahnenstiel; Lingli He; Jeff C Ho; Liza Jenkins; Thomas H Johengen; Kevin C Kuo; Elizabeth Laporte; Xiaojian Liu; Michael R McWilliams; Michael R Moore; Derek J Posselt; R Peter Richards; Donald Scavia; Allison L Steiner; Ed Verhamme; David M Wright; Melissa A Zagorski
Journal:  Proc Natl Acad Sci U S A       Date:  2013-04-01       Impact factor: 11.205

4.  Aggregate Measures of Watershed Health from Reconstructed Water Quality Data with Uncertainty.

Authors:  Yamen M Hoque; Shivam Tripathi; Mohamed M Hantush; Rao S Govindaraju
Journal:  J Environ Qual       Date:  2016-03       Impact factor: 2.751

5.  Differences in phosphorus and nitrogen delivery to the Gulf of Mexico from the Mississippi River Basin.

Authors:  Richard B Alexander; Richard A Smith; Gregory E Schwarz; Elizabeth W Boyer; Jacqueline V Nolan; John W Brakebill
Journal:  Environ Sci Technol       Date:  2008-02-01       Impact factor: 9.028

  5 in total

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