Title of article :
Borehole Optimisation System (BOS) e A case study
assessing options for abstraction of urban groundwater
in Nottingham, UK
Author/Authors :
N.G. Tait a، نويسنده , , *، نويسنده , , R.M. Davison b، نويسنده , , 1، نويسنده , , S.A. Leharne a، نويسنده , , D.N. Lerner، نويسنده ,
Issue Information :
ماهنامه با شماره پیاپی سال 2008
Abstract :
The recognition that urban groundwater is a potentially valuable resource for potable and industrial uses due to growing pressures on perceived
less polluted rural groundwater has led to a requirement to assess the groundwater contamination risk in urban areas from industrial contaminants
such as chlorinated solvents. The development of a probabilistic risk based management tool that predicts groundwater quality at
potential new urban boreholes is beneficial in determining the best sites for future resource development. The Borehole Optimisation System
(BOS) is a custom Geographic Information System (GIS) application that has been developed with the objective of identifying the optimum
locations for new abstraction boreholes. BOS can be applied to any aquifer subject to variable contamination risk. The system is described
in more detail by Tait et al. [Tait, N.G., Davison, J.J., Whittaker, J.J., Leharne, S.A. Lerner, D.N., 2004a. Borehole Optimisation System
(BOS) e a GIS based risk analysis tool for optimising the use of urban groundwater. Environmental Modelling and Software 19, 1111e
1124]. This paper applies the BOS model to an urban PermoeTriassic Sandstone aquifer in the city centre of Nottingham, UK. The risk of
pollution in potential new boreholes from the industrial chlorinated solvent tetrachloroethene (PCE) was assessed for this region. The risk model
was validated against contaminant concentrations from 6 actual field boreholes within the study area. In these studies the model generally underestimated
contaminant concentrations. A sensitivity analysis showed that the most responsive model parameters were recharge, effective porosity
and contaminant degradation rate. Multiple simulations were undertaken across the study area in order to create surface maps indicating areas of
low PCE concentrations, thus indicating the best locations to place new boreholes. Results indicate that northeastern, eastern and central regions
have the lowest potential PCE concentrations in abstraction groundwater and therefore are the best sites for locating new boreholes. These locations
coincide with aquifer areas that are confined by low permeability Mercia Mudstone deposits. Conversely southern and northwestern areas
are unconfined and have shallower depth to groundwater. These areas have the highest potential PCE concentrations. These studies demonstrate
the applicability of BOS as a tool for informing decision makers on the development of urban groundwater resources.
Keywords :
Probabilistic risk modelling , urban groundwater , Borehole Optimisation System , PCE , GIS
Journal title :
Environmental Modelling and Software
Journal title :
Environmental Modelling and Software