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首页> 外文期刊>Environmental Modelling & Software >Borehole Optimisation System (BOS) - A case study assessing options for abstraction of urban groundwater in Nottingham, UK
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Borehole Optimisation System (BOS) - A case study assessing options for abstraction of urban groundwater in Nottingham, UK

机译:钻孔优化系统(BOS)-一个案例研究,评估英国诺丁汉的城市地下水抽取方案

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摘要

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) - 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.
机译:由于人们对污染程度较低的农村地下水的压力越来越大,人们认识到城市地下水是可用于工业和饮用水的潜在宝贵资源,这导致人们需要评估城市地区由工业污染物(如氯化溶剂)引起的地下水污染风险。基于概率风险的管理工具的开发,可以预测潜在的新城市钻孔中的地下水质量,有助于确定未来资源开发的最佳地点。钻孔优化系统(BOS)是一个定制的地理信息系统(GIS)应用程序,其开发目的是为新的抽象钻孔确定最佳位置。 BOS可以应用于受不同污染风险的任何含水层。 Tait等人更详细地描述了该系统。 [Tait,N.G.,Davison,J.J.,Whittaker,J.J.,Leharne,S.A. Lerner,D.N.,2004a。钻孔优化系统(BOS)-基于GIS的风险分析工具,用于优化城市地下水的使用。环境建模与软件19,1111-1124]。本文将BOS模型应用于英国诺丁汉市中心的城市Permo-Triassic砂岩含水层。在该地区评估了工业氯化溶剂四氯乙烯(PCE)对潜在的新井孔造成污染的风险。针对研究区域内6个实际野外钻孔的污染物浓度对风险模型进行了验证。在这些研究中,模型通常低估了污染物的浓度。敏感性分析表明,响应速度最快的模型参数是补给,有效孔隙率和污染物降解率。为了研究表明低PCE浓度区域的表面图,在整个研究区域进行了多次模拟,从而指出了放置新井眼的最佳位置。结果表明,东北,东部和中部地区在提取地下水中潜在的PCE浓度最低,因此是寻找新井眼的最佳场所。这些位置与受低渗透性梅尔西亚泥岩沉积物限制的含水层区域重合。相反,南部和西北地区是无限制的,地下水深度较浅。这些区域具有最高的潜在PCE浓度。这些研究证明了BOS作为向决策者通报城市地下水资源开发的工具的适用性。

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