Event Title

Management of Nitrate Contamination in Ground Water due to Agricultural Activities

Location

Space Dynamics Laboratory

Event Website

http://water.usu.edu/

Start Date

3-26-2004 11:00 AM

End Date

3-26-2004 11:15 AM

Description

Public concerns over groundwater quality have grown significantly in the recent years and have focused increasingly on agriculture as a source of groundwater quality problems. Increasing evidence of nitrate contamination of groundwater beyond the maximum contaminant level has intensified the need for developing protection alternatives. Such alternatives include the restrictions on fertilizer and manure uses. Through the adoption of these alternatives, it is possible to satisfy the groundwater quality objectives in terms of reducing the nitrate occurrences in groundwater. This paper presents an approach to determine the aquifer sustainability in terms of optimal on-ground nitrogen loading distribution such that nitrate concentrations are below the maximum contaminant level. The proposed approach integrates the on-ground nitrogen loadings from different sources, soil transformations of nitrogen, and a groundwater nitrate fate and transport model. In addition, the spatial variability of on-ground nitrogen loadings and the corresponding nitrate leaching to groundwater was considered through the use of the National Land Cover Database. The integrated simulation models were utilized in developing an optimization framework to determine the sustainable on-ground nitrogen loading distribution. By determining these sustainable loadings, protection alternatives can be introduced to areas where nitrogen loadings exceed these loadings. Protection alternatives were developed such that the onground nitrogen loadings will be reduced to the optimal values. The proposed optimization framework utilizes artificial neural networks and genetic algorithm. In order to evaluate the overall efficiency of the proposed alternatives, decision criteria were developed to account for the economic and environmental consequences and a multi-criteria decision analysis was conducted to rank the alternatives. The applicability and practicability of the approach were evaluated at a regional-scale, agriculture-dominated watershed in Washington State.

This document is currently not available here.

Share

COinS
 
Mar 26th, 11:00 AM Mar 26th, 11:15 AM

Management of Nitrate Contamination in Ground Water due to Agricultural Activities

Space Dynamics Laboratory

Public concerns over groundwater quality have grown significantly in the recent years and have focused increasingly on agriculture as a source of groundwater quality problems. Increasing evidence of nitrate contamination of groundwater beyond the maximum contaminant level has intensified the need for developing protection alternatives. Such alternatives include the restrictions on fertilizer and manure uses. Through the adoption of these alternatives, it is possible to satisfy the groundwater quality objectives in terms of reducing the nitrate occurrences in groundwater. This paper presents an approach to determine the aquifer sustainability in terms of optimal on-ground nitrogen loading distribution such that nitrate concentrations are below the maximum contaminant level. The proposed approach integrates the on-ground nitrogen loadings from different sources, soil transformations of nitrogen, and a groundwater nitrate fate and transport model. In addition, the spatial variability of on-ground nitrogen loadings and the corresponding nitrate leaching to groundwater was considered through the use of the National Land Cover Database. The integrated simulation models were utilized in developing an optimization framework to determine the sustainable on-ground nitrogen loading distribution. By determining these sustainable loadings, protection alternatives can be introduced to areas where nitrogen loadings exceed these loadings. Protection alternatives were developed such that the onground nitrogen loadings will be reduced to the optimal values. The proposed optimization framework utilizes artificial neural networks and genetic algorithm. In order to evaluate the overall efficiency of the proposed alternatives, decision criteria were developed to account for the economic and environmental consequences and a multi-criteria decision analysis was conducted to rank the alternatives. The applicability and practicability of the approach were evaluated at a regional-scale, agriculture-dominated watershed in Washington State.

https://digitalcommons.usu.edu/runoff/2004/AllAbstracts/24