Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Quantifying variability within water samples: the need for adequate subsampling.

Ian Donohue1, Kenneth Irvine

  • 1School of Natural Sciences, Zoology Building, Trinity College, University of Dublin, Dublin 2, Ireland. ian.donohue@tcd.ie

Water Research
|August 21, 2007
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Harnessing mmWave signals and machine learning for noninvasive taxonomic classification of insects.

PNAS nexus·2026
Same author

What Drives Compliance with Rules in Community-Based Conservation? Lessons from Maasai Mara, Kenya.

Environmental management·2025
Same author

Shifting cyclone travel speed and its impact on global mangrove ecosystems.

Science advances·2025
Same author

Ecosystem accounting for biodiversity surrounding windfarms.

Journal of environmental management·2025
Same author

Global Change Asymmetrically Rewires Ecosystems.

Ecology letters·2025
Same author

Towards sustainable lake restoration.

The Science of the total environment·2025
Same journal

Non-point source pollution prediction and dynamics simulation in urban runoff: a physics-informed neural network approach.

Water research·2026
Same journal

A multivariate water quality forecasting model with dynamic variable selection and dissolved oxygen physical-consistency constraints.

Water research·2026
Same journal

Spectroscopic and multivariate analysis insights into the DOM composition and distribution in a full-scale photovoltaic wastewater zero-liquid discharge system.

Water research·2026
Same journal

Assessing climate change-induced precipitation effects on the long-term reliability of common final landfill cover systems.

Water research·2026
Same journal

Synergetic piezo-photocatalytic tuning internal electric field in S-scheme heterojunction for highly efficient tetracycline degradation and hydrogen production.

Water research·2026
Same journal

Mimosa-inspired dual-responsive flocculant with controllable hydrophobicity/hydrophilicity reconstruction for the purification of triclosan containing emulsified wastewater.

Water research·2026
See all related articles

Accurate water quality monitoring requires analyzing multiple subsamples. A single water sample is insufficient due to high within-sample variability, especially in rivers, impacting reliable environmental management.

Area of Science:

  • Environmental Science
  • Analytical Chemistry
  • Water Resource Management

Background:

  • Effective water quality management relies on accurate chemical indicator measurements.
  • Current monitoring practices often use single samples, neglecting spatial and temporal variability.
  • Logistic and financial constraints limit comprehensive water sampling strategies.

Purpose of the Study:

  • To assess total sample variability for key water quality indicators.
  • To quantify the contribution of within-sample heterogeneity to total variability.
  • To determine the adequacy of single samples for robust water quality assessment.

Main Methods:

  • Analysis of chlorophyll a, total phosphorus, total nitrogen, soluble molybdate-reactive phosphorus, and dissolved inorganic nitrogen.

Related Experiment Videos

  • Comparison of sample variability between rivers and lakes.
  • Evaluation of the effect of filtration on within-sample heterogeneity.
  • Statistical analysis of analytical and within-sample variability.

    • Main Results:

    • Total sample variability for key indicators is high and varies significantly over time and among determinands.
    • Within-sample heterogeneity contributes substantially (62%-100%) to total sample variability.
    • Within-sample heterogeneity is significantly higher in river samples than lake samples and is reduced by filtration.

    Conclusions:

    • Single water samples, or even two subsamples, are inadequate for reliable surface water quality detection.
    • High within-sample heterogeneity necessitates a revised sampling strategy.
    • A minimum of three subsamples per waterbody sample is recommended for robust quantification and variability assessment.