Stochastic assimilation of geophysical and hydrological data for the estimation of hydraulic conductivity

用于估算导水率的地球物理和水文数据的随机同化

• 批准号: 385996-2010
• 负责人: Irving, James
• 金额: $ 1.46万
• 依托单位: University of Guelph
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2010
• 资助国家: 加拿大
• 起止时间: 2010-01-01 至 2011-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=463632
• 关键词: Stochastic; assimilation; geophysical; hydrological; data

Geophysical methods offer much potential in hydrology because of their ability to image subsurface properties with a resolution and degree of spatial coverage unattainable with traditional hydrological measurements. This has resulted in a recent and rapid expansion of the new and interdisciplinary field of "hydrogeophysics". The overall goal of the proposed research program is to address a key issue in current hydrogeophysical research, which is how to best assimilate diverse sources of geophysical, hydrological, and geological data in order to estimate subsurface hydrological properties within a framework of uncertainty. Two student projects are proposed to begin work in this domain at the University of Guelph, both of which have the general goal of estimating the spatial configuration of hydraulic conductivity in heterogeneous alluvial aquifers, which is the dominant control on groundwater flow and contaminant transport. The first project will work at the local (~10m) scale, and will involve the stochastic assimilation of tracer-test concentration measurements and time-lapse electrical resistivity data using a Bayesian Markov-chain-Monte-Carlo methodology. Here, the geophysical and hydrological process models will be coupled to provide a link between the resistivity measurements and hydraulic conductivity. The second project will work at a larger (~100m) scale, and will involve the use of multiple geophysical methods and cluster analysis techniques to first zone the subsurface into distinct units that are assumed to have constant hydrological properties. Then, using larger-scale hydrological data, the properties of the zones and their uncertainties will be estimated. Work on both of these projects will begin with numerical "synthetic" studies, and will be fully tested in 2-D before moving to 3-D applications. All results obtained will be evaluated in terms of their ability to reduce hydrological prediction uncertainty. Over the longer term, this research will lead to additional student projects involving testing of the proposed methodologies in the field as well as detailed investigation of issues expected to be crucial for meaningful uncertainty estimates, such as the reliable assessment of data and model structural errors.

地球物理方法在水文学中具有很大的潜力，因为它们能够以传统水文测量无法达到的分辨率和空间覆盖度对地下特性进行成像。 这导致了“水文物理学”这一新的跨学科领域最近的迅速扩展。 拟议的研究计划的总体目标是解决当前水文地球物理研究中的一个关键问题，即如何最好地吸收地球物理，水文和地质数据的不同来源，以估计地下水文特性的不确定性的框架内。 两个学生项目提出了开始在这一领域的工作在圭尔夫大学，这两个都有估计的空间配置的水力传导性在非均质冲积含水层，这是地下水流和污染物运输的主要控制的总体目标。 第一个项目将在当地（~ 10米）规模进行，并将涉及使用贝叶斯马尔可夫链-蒙特-卡罗方法随机同化示踪剂测试浓度测量值和时间推移电阻率数据。 在这里，地球物理和水文过程模型将被耦合，以提供电阻率测量和水力传导率之间的联系。 第二个项目将在更大（~ 100米）的规模上工作，并将涉及使用多种地球物理方法和聚类分析技术，首先将地下区域划分为假定具有恒定水文特性的不同单元。 然后，使用更大规模的水文数据，区域的属性和它们的不确定性将被估计。 这两个项目的工作将开始与数字“合成”的研究，并将在2-D进行充分的测试，然后再转移到3-D的应用。 将根据其减少水文预测不确定性的能力来评价所获得的所有结果。 从长远来看，这项研究将导致额外的学生项目，涉及在该领域的拟议方法的测试，以及对预计对有意义的不确定性估计至关重要的问题的详细调查，如数据和模型结构误差的可靠评估。