Data Integration to Significantly Improve Hydraulic Tomography and Groundwater Modelling in Complex Geologic Media

数据集成可显着改善复杂地质介质中的水力层析成像和地下水建模

• 批准号: RGPIN-2017-03859
• 负责人: Illman, Walter
• 金额: $ 1.97万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=634197
• 关键词: Data; Integration; Significantly; Improve; Hydraulic

Groundwater models have become indispensable in water supply assessment and contaminant transport studies. The availability of various models, their improved capabilities, and ever-increasing computational resources have advanced models closer to reality. They are becoming increasingly relied upon to make important decisions that have business, policy and societal consequences. One key ingredient to building more reliable models is employing more accurate flow parameters such as hydraulic conductivity (

地下水模型已成为供水评价和污染物运移研究中不可或缺的组成部分。各种模型的可用性，其改进的能力，以及不断增加的计算资源，使先进的模型更接近现实。在作出具有商业、政策和社会影响的重要决策时，人们越来越依赖他们。建立更可靠模型的一个关键因素是采用更准确的流动参数，如水力传导率（