Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Typical Model Studies

Typical Model Studies

Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.

Uncertainty: Overview

Uncertainty: Overview

In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...

Design Example: Creating a Hydraulic Model of a Dam Spillway

Design Example: Creating a Hydraulic Model of a Dam Spillway

Scaled hydraulic models of dam spillways provide a practical way to replicate and study the intricate flow dynamics of these structures. Often built to a 1:15 ratio, these models allow for observing critical water behavior, such as velocity distribution, flow patterns, and energy dissipation.

Modeling and Similitude

Modeling and Similitude

Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...

Testing Water Quality

Testing Water Quality

When the quality of water for concrete preparation is uncertain, its impact on the setting time of cement and compressive strength of mortar is assessed by comparison with de-ionized or distilled water benchmarks. American Society for Testing and Materials (ASTM) C1602 requires the setting times to be within 90 minutes of the control, British Standard (BS) 3146:1980 allows a 30-minute variance in the initial setting, while British Standards European Norm (BS EN) 1008 specifies initial setting...

You might also read

Related Articles

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

Sort by

Same author

ORIGIN-1 trial: study protocol for an organoid-guided N-of-1 trial evaluating CFTR modulator response in cystic fibrosis with rare non-F508del mutations.

Trials·2026

Same author

Total herbivore exclusion alters plant species dominance and trait expression in endangered grassy woodlands.

Ecology·2026

Same author

Modelling land use influence on polymer-specific microplastics abundance and transportation from terrestrial to aquatic environments.

Environmental pollution (Barking, Essex : 1987)·2026

Same author

Catchment characteristics and land-use influence on microplastics distribution in freshwater sediments.

Environmental pollution (Barking, Essex : 1987)·2026

Same author

Polydopamine-Mediated Grafting of Cationic Polymer Brushes for Adsorption of Fluorinated Compounds.

Chemistry (Weinheim an der Bergstrasse, Germany)·2026

Same author

Targeting degraded hotspots in riparian corridors for rehabilitation based on hydrological, ecological, natural and anthropogenic indicators.

Journal of environmental management·2026

Search research articles

Related Experiment Video

Updated: Mar 17, 2026

Vegetated Treatment Systems for Removing Contaminants Associated with Surface Water Toxicity in Agriculture and Urban Runoff

Vegetated Treatment Systems for Removing Contaminants Associated with Surface Water Toxicity in Agriculture and Urban Runoff

Published on: May 15, 2017

Assessing uncertainty in stormwater quality modelling.

Buddhi Wijesiri¹, Prasanna Egodawatta¹, James McGree¹

¹Science and Engineering Faculty, Queensland University of Technology (QUT), GPO Box 2434, Brisbane, 4001, Queensland, Australia.

|July 18, 2016

Summary

This summary is machine-generated.

Urban stormwater pollution mitigation is challenging due to unreliable models. This study quantifies build-up and wash-off process uncertainty, improving stormwater quality predictions and mitigation strategy design.

Keywords:

Particle size Pollutant build-up Pollutant wash-off Process uncertainty Stormwater pollutant processes Stormwater quality

More Related Videos

Watershed Planning within a Quantitative Scenario Analysis Framework

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Published on: September 26, 2017

Related Experiment Videos

Last Updated: Mar 17, 2026

Vegetated Treatment Systems for Removing Contaminants Associated with Surface Water Toxicity in Agriculture and Urban Runoff

Vegetated Treatment Systems for Removing Contaminants Associated with Surface Water Toxicity in Agriculture and Urban Runoff

Published on: May 15, 2017

Watershed Planning within a Quantitative Scenario Analysis Framework

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Published on: September 26, 2017

Area of Science:

Environmental Engineering
Water Resource Management
Urban Hydrology

Background:

Effective urban stormwater management faces challenges due to the unreliability of catchment-scale stormwater quality models.
Assessing model-generated uncertainty is crucial for informed decision-making in pollution mitigation.
Existing uncertainty assessment methods often fail to adequately address process uncertainty in build-up and wash-off.

Purpose of the Study:

To quantitatively assess the uncertainty associated with build-up and wash-off processes in urban stormwater quality modelling.
To investigate how process uncertainty influences stormwater quality predictions.
To provide insights for designing more effective stormwater pollution mitigation strategies.

Main Methods:

Characterizing variability in build-up and wash-off processes across different particle size ranges.
Incorporating quantified process uncertainties into catchment stormwater quality predictions.
Analyzing the impact of build-up versus wash-off process uncertainty on model outputs.

Main Results:

Variability in build-up and wash-off processes, particularly concerning particle size, directly leads to process uncertainty.
Accounting for process uncertainty significantly influences the uncertainty bounds of predicted stormwater quality.
Build-up process uncertainty has a greater impact on stormwater quality predictions than wash-off process uncertainty.

Conclusions:

Decision-making for mitigation strategies should prioritize addressing dry-weather pollutant accumulation variations.
The influence of process uncertainty on predictions varies with storm event characteristics (intensity, duration, volume) and Runoff-Catchment Area ratio.
Selecting appropriate storm events for mitigation strategy design requires consideration of both event characteristics and the impact of process uncertainty on predictions.