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 Concept Videos

Virtual Work01:20

Virtual Work

1.4K
The principle of virtual work states that if a body is in static and dynamic equilibrium, then the sum of all the virtual work done by all external forces and couple moments for any given virtual displacement must be zero.
In static equilibrium, a body can experience an imaginary or virtual movement, such as displacement or rotation. The virtual work done by a force is equal to the dot product of force and virtual displacement in the direction of the force. When it comes to virtually rotating a...
1.4K
Variability: Analysis01:11

Variability: Analysis

520
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
520
Random Variables01:09

Random Variables

17.9K
A random variable is a single numerical value that indicates the outcome of a procedure. The concept of random variables is fundamental to the probability theory and was introduced by a Russian mathematician, Pafnuty Chebyshev, in the mid-nineteenth century.
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
17.9K
Graphs of Equations in Two Variables01:30

Graphs of Equations in Two Variables

253
An equation with two variables, typically written in the form y = f(x) or Ax + By = C, describes a relationship between quantities represented by x and y. Each solution to such an equation is an ordered pair (x, y) that satisfies the equation when substituted. These pairs can be represented graphically to understand the variables' relationship visually.A common technique for constructing the graph of a two-variable equation is to create a value table. Begin by choosing several values for the...
253
Variables Affecting Phosphorescence and Fluorescence01:26

Variables Affecting Phosphorescence and Fluorescence

1.5K
Fluorescence and phosphorescence are essential phenomena in fields like analytical chemistry, biological imaging, and materials science, where they detect molecular properties and visualize cellular structures. Understanding the variables that influence these luminescent behaviors is crucial for maximizing accuracy and efficiency in their applications. These variables can broadly be grouped into chemical structure, solvent properties, and external conditions, each playing a distinct role in...
1.5K
Bioavailability Enhancement: Determination and Conceptual Approaches in Overcoming Bioavailability Problems01:22

Bioavailability Enhancement: Determination and Conceptual Approaches in Overcoming Bioavailability Problems

212
Body:Bioavailability is a critical pharmacological concept that measures the extent and rate at which an active drug ingredient or therapeutic moiety enters the systemic circulation, remaining unchanged. It's a pivotal factor in determining a drug's efficacy and safety.The Biopharmaceutics Classification System (BCS) plays an essential role in drug development by categorizing drugs into four classes based on their solubility and permeability. This classification aids in understanding drug...
212

You might also read

Related Articles

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

Sort by
Same author

Modeling an integrated urban wastewater system to assess (micro-)pollutant discharge under dry- and wet-weather: mitigation strategies and climate change scenarios.

Journal of environmental management·2026
Same author

<i>LevelWAN</i>: a cost-effective, open-source IoT system for water level monitoring in highly dynamic aquatic environments.

HardwareX·2025
Same author

The role of open data in regulating combined sewer overflows.

Water science and technology : a journal of the International Association on Water Pollution Research·2025
Same author

Laboratory performance assessment of low-cost water level sensor for field monitoring in the tropics.

Water research X·2025
Same author

RISMEAU dataset: Pharmaceuticals and biocides concentrations in urban and agricultural sludge, amended soil and leachate and their environmental impacts.

Data in brief·2024
Same author

From the highway to receiving water bodies: identification and simultaneous quantification of small microplastics (< 100 µm) in highway stormwater runoff.

Environmental science and pollution research international·2024

Related Experiment Video

Updated: Feb 5, 2026

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
09:10

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Published on: August 5, 2021

2.3K

Revisiting conceptual stormwater quality models by reconstructing virtual state variables.

Santiago Sandoval1, Luca Vezzaro2, Jean-Luc Bertrand-Krajewski1

  • 1Université de Lyon, INSA Lyon, DEEP, EA 7429, 34 avenue des Arts, F-69621 Villeurbanne cedex, France

Water Science and Technology : a Journal of the International Association on Water Pollution Research
|September 13, 2018
PubMed
Summary

Traditional stormwater models struggle to represent pollutant loads from many rainfall events. This study introduces a Bayesian approach to better reconstruct virtual state variables, improving understanding of total suspended solids pollutographs.

More Related Videos

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells
12:49

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Published on: September 28, 2019

13.4K
A Postoperative Evaluation Guideline for Computer-Assisted Reconstruction of the Mandible
10:42

A Postoperative Evaluation Guideline for Computer-Assisted Reconstruction of the Mandible

Published on: January 28, 2020

7.0K

Related Experiment Videos

Last Updated: Feb 5, 2026

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
09:10

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Published on: August 5, 2021

2.3K
A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells
12:49

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Published on: September 28, 2019

13.4K
A Postoperative Evaluation Guideline for Computer-Assisted Reconstruction of the Mandible
10:42

A Postoperative Evaluation Guideline for Computer-Assisted Reconstruction of the Mandible

Published on: January 28, 2020

7.0K

Area of Science:

  • Environmental Science
  • Hydrology
  • Water Quality Modeling

Background:

  • Traditional wash-off models, like the rating curve (RC) model, are commonly used to represent stormwater total suspended solids (TSS) pollutographs.
  • These models often assume antecedent dry weather conditions influence pollutant loads, a factor this study investigates.
  • A significant portion of measured rainfall events show limitations in representation by traditional models.

Purpose of the Study:

  • To propose a Bayesian non-informative reconstruction method for virtual state variables in TSS pollutograph modeling.
  • To identify and analyze the limitations of traditional wash-off models, specifically the RC model, in representing stormwater pollutant loads.
  • To evaluate the interpretability and predictability of the proposed Bayesian reconstruction method.

Main Methods:

  • Utilized data from 255 rainfall events in a 185 ha French urban catchment.
  • Performed event-based analyses to compare traditional RC model performance against measured TSS pollutographs.
  • Applied Bayesian non-informative reconstruction to model virtual state variables for events not adequately represented by the RC model.

Main Results:

  • The traditional RC model failed to adequately represent essential processes for 56% of the analyzed rainfall events.
  • Model performance issues were not solely linked to antecedent dry weather conditions.
  • Proposed Bayesian reconstructions showed intra-event identifiability but lacked interpretability in terms of traditional wash-off concepts (e.g., a unique, time-decreasing virtual mass) due to unrepeatability and low cross-event predictive capacity.

Conclusions:

  • Traditional wash-off models have significant limitations in capturing the complexity of stormwater TSS pollutographs across diverse rainfall events.
  • Bayesian reconstruction offers a way to identify processes missed by simpler models but requires further development for practical interpretation and prediction.
  • The findings challenge assumptions about antecedent conditions and highlight the need for more robust modeling approaches for urban stormwater quality.