Related Experiment Video
Updated: May 5, 2026
10:35
A Protocol for Conducting Rainfall Simulation to Study Soil Runoff
Published on: April 3, 2014
21.9K
Rainfall-induced fecal indicator organisms transport from manured fields: model sensitivity analysis
Gonzalo Martinez1, Yakov A Pachepsky2, Gene Whelan3
1Department of Agronomy, University of Cordoba, 14071, Cordoba, Spain; USDA-ARS- Environmental Microbial and Food Safety Lab, Beltsville, MD, 20705, USA.
Environment International
|December 3, 2013
Summary
Environmental factors like soil saturation and rainfall significantly impact fecal indicator organism (FIOs) transport from fields. Understanding these factors is key to predicting microbial pollution and reducing waterborne disease risks.
Area of Science:
- Environmental Science
- Microbiology
- Water Quality Management
Background:
- Surface water microbial quality is critical due to food- and waterborne disease outbreaks.
- Fecal indicator organisms (FIOs) are used to assess microbial pollution levels.
- Predictive models are essential for managing microbial pollution and associated disease risks.
Purpose of the Study:
- To conduct a sensitivity analysis of the KINEROS/STWIR model for FIO transport.
- To identify input variables that significantly influence FIO transport uncertainty.
- To understand the impact of environmental and manure properties on FIO removal from fields.
Main Methods:
- Global sensitivity analysis using Sobol' indices and regression trees.
- Model parameterization based on experimental data and public information.
- Exploration of interactions between model input parameters.
Main Results:
- Environmental factors (soil saturation, rainfall duration/intensity) were the most influential on FIO transport.
- Soil and manure properties had a lower impact, except for FIO release kinetics.
- Regression trees effectively visualized sensitivity across different input domains.
Conclusions:
- Environmental conditions are primary drivers of FIO transport from manured fields.
- Characterizing FIO release kinetics is crucial for accurate transport prediction.
- Large-scale FIO transport estimates can be achieved using publicly available data.
