Tait, N. G., Davison, R. M., Leharne, S. A. and Lerner, D. N. (2008) Borehole Optimisation System (BOS) - a case study assessing options for abstraction of urban groundwater in Nottingham, UK. Environmental Modelling & Software, 23 (5). pp. 611-621. ISSN 1364-8152 (doi:https://doi.org/10.1016/j.envsoft.2007.09.001)

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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., Lehame, S.A. Lerner, D.N., 2004a. Borehole Optimisation System (BOS) - a GIs based risk analysis tool for optimising the use of urban groundwater. Environmental Modelling and Software 19, 1111-1124]. This paper applies the BOS model to an urban Permo-Triassic 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. (c) 2007 Elsevier Ltd. All rights reserved.

Item Type:	Article
Uncontrolled Keywords:	borehole optimisation system, GIS, PCE, probabilistic risk modelling, urban groundwater
Subjects:	Q Science > QD Chemistry T Technology > TD Environmental technology. Sanitary engineering
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science > School of Science (SCI)
Related URLs:	Publisher
Last Modified:	11 Feb 2020 12:53
URI:	http://gala.gre.ac.uk/id/eprint/2225

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