RUI: Predicting Transport Through Heterogeneous Facies Assemblages: Geostatistical Anatomy of Buried-Valley Aquifiers, II

RUI：通过非均质相组合预测输运：埋谷含水层的地统计解剖学，II

• 批准号: 9628299
• 负责人: Robert Ritzi
• 金额: $ 6.61万
• 依托单位: Wright State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-09-01 至 1998-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9628299&HistoricalAwards=false
• 关键词: RUI; Predicting; Transport; Through; Heterogeneous

9628299 Ritzi Contaminant problems have created the need to understand how hydraulic conductivity (K) is distributed in aquifer systems. Extreme-value pathways exert a dominant physical control on contaminant transport, and thus the boundary between high-K and low-K materials (hydrofacies) must be quantified. Although the exact geometry of the hydrofacies can only be determined by a prohibitive amount of subsurface information, stochastic methods such as conditional indicator simulation provide a way to compute a number of realizations of hydrofacies distributions that honor available data at their locations, with specified functions for the principal directions of spatial correlation of the hydrofacies, the scale of correlation in these directions, and the proportions. Running transport simulations using a large number of these realizations and examining the central tendency and variance of simulated contaminant travel times, or the simulated contaminant pathways, can give insight into how contaminants will move through the real system. These simulations can also be incorporated into a formal decision-analysis framework. However, the field data at a specific site commonly are insufficient for the purpose of defining the spatial correlation and proportions of the hydrofacies directly. Therefore, analog sites that are data rich need to be studied in order to find models for spatial correlation and proportions of hydrofacies that, on the basis of similar geology, can be transferred to data-poor sites. Indeed, one of the research needs identified by the National Research Council in Alternatives for Ground Water Cleanup, is the development of statistical models representing common geologic environments, which can be used to assess the variability of aquifer properties and thereby improve the success of aquifer restoration (NRC, 1994, p. 73). The proposed research will develop statistical models for aquifer properties in buried-valley aquifers, which occur across the central a nd western glaciated plains of North America and are vital to the water resources of the region. In such glacially derived aquifers, it is common to have low-K facies (e.g., till or lacustrine clay) juxtaposed with high-K facies (e.g., sand and gravel outwash). This is a renewal proposal. In the prior phase, several locations were studied in a buried-valley aquifer system located in Ohio, with the successful development of models for the hydrofacies distribution, proportions, principal directions of spatial correlation, and correlation scale in these directions. These statistical models were linked to the deposition processes that created the aquifer system, and therefore are likely to be applicable to other locations in the aquifer, and to other aquifer systems where similar depositional processes have operated. However, hydrofacies models are most useful when based on the features of numerous well-studied examples. The generality and usefulness of quantitative geostatistical models will likewise increase with their numbers, if more data-rich analogs are examined. One goal of this renewal proposal is to develop new geostatistical models for a buried-valley aquifer system in Indiana. However, the main focus of this work will be to critically evaluate methods of linking spatial correction of hydrologic parameters and geologic structure. The transition probability has been shown to be an even more interpretable representation of spatial correlation than the variography used in the prior phase. Thus the transition probability may provide a new tool for linking spatial correlation and deposition processes. The innovative aspect of this work is that it will provide a way to test the hypothesis that generic hydrofacies models can be developed for a specific class of aquifers. This will be the first comparison of spatial correlation of hydrogeologic parameters among aquifers, and is part of the longer-term goal of developing a catalogue of quantitative hydrofacies. ??

9628299 Ritzi 污染问题产生了需要了解如何水力传导性（K）在含水层系统中的分布。 极端值路径施加污染物输运的主要物理控制，因此，高K和低K材料（水文相）之间的边界必须量化。 虽然水相的精确几何形状只能由大量的地下信息来确定，但诸如条件指示模拟的随机方法提供了一种计算水相分布的多个实现的方式，该水相分布荣誉其位置处的可用数据，具有用于水相的空间相关性的主要方向、这些方向上的相关性的尺度和比例的指定函数。 运行传输模拟使用大量的这些实现，并检查模拟污染物的传播时间，或模拟污染物的路径的集中趋势和方差，可以给洞察污染物将如何通过真实的系统。 这些模拟也可以纳入正式的决策分析框架。 然而，在一个特定的网站现场数据通常是不够的，以确定的空间相关性和比例的目的，直接水文相。 因此，需要研究数据丰富的模拟站点，以找到空间相关性和水文相比例的模型，根据相似的地质情况，可以将其转移到数据贫乏的站点。 事实上，全国地下水替代办法研究理事会确定的研究需要之一是开发代表共同地质环境的统计模型，可用于评估含水层特性的可变性，从而提高含水层恢复的成功率（NRC，1994年，第73页）。 拟议的研究将开发埋藏谷含水层的含水层特性的统计模型，这些含水层发生在北美中部和西部的冰川平原上，对该地区的水资源至关重要。 在这种冰川含水层中，通常具有低K相（例如，冰碛或湖相粘土）与高K相（例如，砂和砾石沉积物）。 这是一个更新的建议。 在前一阶段，研究了位于俄亥俄州的埋藏谷含水层系统中的几个位置，成功开发了水文相分布、比例、空间相关性的主要方向以及这些方向的相关尺度的模型。 这些统计模型与形成含水层系统的沉积过程有关，因此可能适用于含水层的其他地点，也适用于有类似沉积过程的其他含水层系统。 然而，水文相模型是最有用的，当基于许多良好的研究实例的功能。 如果研究更多数据丰富的类似物，定量地质统计模型的通用性和实用性也将随着其数量的增加而增加。 该更新提案的一个目标是为印第安纳州的埋藏谷含水层系统开发新的地质统计模型。 然而，这项工作的主要重点将是严格评价将水文参数的空间校正与地质结构联系起来的方法。 转移概率已被证明是一个更可解释的空间相关性比变差图中使用的前一阶段的表示。 因此，转移概率可以提供一个新的工具，连接空间相关性和沉积过程。 这项工作的创新之处在于，它将提供一种方法来检验这一假设，即可以为特定类别的含水层开发通用水文相模型。 这将是第一次比较含水层之间水文地质参数的空间相关性，也是编制定量水文相目录这一长期目标的一部分。 ??