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Related Concept Videos

Typical Model Studies01:30

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.
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

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...
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...
Gravimetry: Overview01:05

Gravimetry: Overview

Gravimetric analysis is a quantitative method where the analyte is isolated and weighed directly or after conversion into a substance of known composition. Gravimetric analysis can be classified as precipitation, electrogravimetry, volatilization, and particulate gravimetry, based on the method used to isolate the analyte.
In precipitation gravimetry, the analyte is converted into a precipitate and weighed. For example, the silver content in a sample can be estimated by precipitating and...
Manipulation and Analysis01:21

Manipulation and Analysis

GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
Design Example: Creating a Hydraulic Model of a Dam Spillway01:21

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.

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Related Experiment Video

Updated: Jun 21, 2026

Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

Global sensitivity analysis techniques for probabilistic ground water modeling.

Srikanta Mishra1, Neil Deeds, Greg Ruskauff

  • 1INTERA Inc., Austin, TX 78754, USA. smishra@intera.com

Ground Water
|August 12, 2009
PubMed
Summary

Global sensitivity analysis methods effectively explore parameter variations and model outcomes. This study details three techniques: stepwise rank regression, mutual information, and classification trees, for robust groundwater modeling.

Related Experiment Videos

Last Updated: Jun 21, 2026

Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

Area of Science:

  • Environmental Science
  • Hydrology
  • Computational Modeling

Background:

  • Local sensitivity analysis is limited to reference points.
  • Global sensitivity analysis (GSA) examines full parameter ranges.
  • GSA is crucial for understanding complex model behavior.

Purpose of the Study:

  • Introduce and explain three GSA techniques.
  • Demonstrate their application in groundwater modeling.
  • Compare GSA with local sensitivity analysis.

Main Methods:

  • Stepwise rank regression for identifying variance contributors.
  • Mutual information (entropy) for non-monotonic input-output relationships.
  • Classification trees for identifying drivers of extreme outputs.
  • Integration with Monte Carlo simulations.

Main Results:

  • Stepwise rank regression identifies key input variables.
  • Mutual information quantifies complex input-output associations.
  • Classification trees pinpoint drivers of extreme model outcomes.
  • GSA methods provide comprehensive insights.

Conclusions:

  • GSA techniques are superior to local methods for full-range analysis.
  • Recommended for practical application in groundwater modeling.
  • Enhances understanding of model sensitivity and parameter importance.