利用地下水反演模型研究某饮用水产地的含水层非均质性

IF 4.6 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Martijn D. van Leer , Willem J. Zaadnoordijk , Alraune Zech , Jasper Griffioen , Marc F.P. Bierkens
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引用次数: 0

摘要

本文研究了从饮用水井场收集的数据是否可以确定引水层的地质统计学性质。开发了一个适用于任何具有抽水和地下水头数据的饮用水抽取点的工作流程。利用来自荷兰Budel的数据,建立了一个分层地下水流动模型,并在水头上进行了校准。考虑到不同的异质性参数,对aquitard产生了大量的实现。这些模拟被升级到流动模型的网格,并评估了它们与观察到的水头的拟合。结果表明,即使许多组合重现观测到的头部,也可以确定最佳的地质统计参数。这些参数可用于参数化区域地下水流动模型。颗粒跟踪模拟表明,非均质性减少了污染物的突破次数,同时也减少了通过进水层的总流量。这些研究结果强调,在饮用水生产场所进行风险评估时,需要考虑水质的异质性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Investigating aquitard heterogeneity by inverse groundwater modelling at a drinking water production site
This study investigates whether geostatistical properties of aquitards can be determined from data collected at a drinking water well field. A workflow adaptable to any drinking water extraction site with pumping and groundwater head data is developed. Using data from Budel, the Netherlands, a layered groundwater flow model is constructed and calibrated on hydraulic heads. A large number of realizations are generated for the aquitard, considering various heterogeneity parameters. These simulations are upscaled to the grid of the flow model, and their fit to observed heads is evaluated. Results show that optimal geostatistical parameters can be identified, even though many combinations reproduce observed heads. These parameters can be used to parameterize regional groundwater flow models. Particle tracking simulations show heterogeneity decreases contaminant breakthrough times while also decreasing the total flow through the aquitard. These findings emphasize the need to consider aquitard heterogeneity in risk assessments at drinking water production sites.
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来源期刊
Environmental Modelling & Software
Environmental Modelling & Software 工程技术-工程:环境
CiteScore
9.30
自引率
8.20%
发文量
241
审稿时长
60 days
期刊介绍: Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.
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