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Fuzzy rule based estimation of agricultural diffuse pollution concentration in streams
1Department of Civil Engineering, Motilal Nehru National Institute of Technology, Allahabad-211 004, India. rajm@mnnit.ac.in
Journal of Environmental Science & Engineering
|March 20, 2009
Summary
Agricultural runoff pollutes streams with diffuse pollutants. A fuzzy rule-based model effectively estimates herbicide concentrations in streams, addressing data uncertainties for improved water quality predictions.
Area of Science:
- Environmental Science
- Water Resource Management
- Computational Hydrology
Background:
- Agricultural runoff is a significant source of diffuse pollution in surface waters, including nutrients, pesticides, and herbicides.
- Predicting stream water quality is complex due to uncertainties in chemical application, transport, and potential measurement errors in input-output data.
- Diffuse pollution from agricultural fields poses a serious concern for water managers and environmental researchers globally.
Purpose of the Study:
- To develop and evaluate a fuzzy rule-based model for estimating herbicide concentrations in streams.
- To address uncertainties inherent in the relationship between agricultural chemical inputs and stream pollutant outputs.
- To utilize fuzzy set properties for reliable stream quality predictions, even with limited data.
Main Methods:
- Application of fuzzy set theory and fuzzy rule-based modeling to handle input uncertainties.
- Development of models using data from the White River Basin, a part of the Mississippi River system.
- Incorporation of overlapping membership functions to manage variability in input parameters like chemical characteristics and application area.
Main Results:
- The fuzzy rule-based model successfully estimated the concentration of the herbicide atrazine in stream water.
- The methodology demonstrated an encouraging performance in predicting pollutant concentrations.
- Fuzzy logic effectively managed uncertainties in the input-output relationships of agricultural pollutant transport.
Conclusions:
- Fuzzy rule-based models are a viable approach for managing uncertainties in predicting stream water quality impacted by agricultural runoff.
- The developed methodology shows promise for water resource management and environmental research, particularly in data-scarce situations.
- Accurate estimation of herbicide concentrations is achievable using fuzzy logic, contributing to better environmental protection strategies.
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