Keywords

Diffuse pollution; groundwater contamination; nitrate; drinking water borehole; management tools.

Location

Session D4: Water Resource Management and Planning - Modelling and Software for Improving Decisions and Engaging Stakeholders

Start Date

12-7-2016 9:30 AM

End Date

12-7-2016 9:50 AM

Abstract

Nowadays, the quantitative evaluation of the impact of agricultural practices on groundwater quality and the estimation of the underground residence time of contaminants can be achieved by solving the advection, dispersion, and reaction differential equations. However, the application of these models at the aquifer scale is always difficult because it requires a large amount of data to be consistent with field observations. Thus, in practice numerical modelling is mostly incompatible with the financial support of water managers and the time-frame imposed by the authorities for groundwater vulnerability assessments.

This note presents an operational approach to model contaminant migration from soil to drinking water boreholes. The proposed model used the residence time distribution concept and was designed to help stakeholders assess the quantitative impact of agricultural policies on underground water quality. First, the model is built by an expert, to define the underground properties describing underground pollutant migration. The model can be calibrated with historical datasets. Then an interface is proposed to enable stakeholders to estimate the impact of a future agricultural practice on the water quality. These estimations are based on scenarios of contaminant release (such as nitrate flux under the crops) defined and applied on the different vulnerability areas delimited on the watershed by the stakeholder himself. The interface allows stakeholders to interactively define the areas of vulnerability. The possibilities of this approach are presented here through the example of the “La Saussaye” borehole water supply draining the Beauce limestone aquifer (Chartres, France), where nitrate has increased since the 1980s.

 
Jul 12th, 9:30 AM Jul 12th, 9:50 AM

Engaging Stakeholders in assessing the impact of agricultural practice on groundwater quality: the Residence Time Distribution model (RTD)

Session D4: Water Resource Management and Planning - Modelling and Software for Improving Decisions and Engaging Stakeholders

Nowadays, the quantitative evaluation of the impact of agricultural practices on groundwater quality and the estimation of the underground residence time of contaminants can be achieved by solving the advection, dispersion, and reaction differential equations. However, the application of these models at the aquifer scale is always difficult because it requires a large amount of data to be consistent with field observations. Thus, in practice numerical modelling is mostly incompatible with the financial support of water managers and the time-frame imposed by the authorities for groundwater vulnerability assessments.

This note presents an operational approach to model contaminant migration from soil to drinking water boreholes. The proposed model used the residence time distribution concept and was designed to help stakeholders assess the quantitative impact of agricultural policies on underground water quality. First, the model is built by an expert, to define the underground properties describing underground pollutant migration. The model can be calibrated with historical datasets. Then an interface is proposed to enable stakeholders to estimate the impact of a future agricultural practice on the water quality. These estimations are based on scenarios of contaminant release (such as nitrate flux under the crops) defined and applied on the different vulnerability areas delimited on the watershed by the stakeholder himself. The interface allows stakeholders to interactively define the areas of vulnerability. The possibilities of this approach are presented here through the example of the “La Saussaye” borehole water supply draining the Beauce limestone aquifer (Chartres, France), where nitrate has increased since the 1980s.