Model Reduction in Groundwater Modeling

地下水建模中的模型简化

• 批准号: 0910507
• 负责人: William W-G. Yeh
• 金额: $ 15.56万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0910507&HistoricalAwards=false
• 关键词: Model; Reduction; Groundwater; Modeling

This is a proposal submitted to both NSF and ARO for joint support, with each agency being asked to fund separate but related facets of the proposal. We propose to develop techniques which can be used for model reduction, whereby a complex full-model is replaced with a smaller simpler approximation that produces outputs within a desired degree of accuracy. Our proposed method combines the data driven and model driven methods in that it makes use of input/output data relationships as well as incorporates the physics of the model. The overriding objective of this proposal is to formulate and generalize model reduction via proper orthogonal decomposition in groundwater modeling in one, two, and three dimensions and to develop a protocol for snapshot selection based on the structure of both the governing equation and the parameters of the model. We will also propose procedures whereby the reduced-model is utilized for groundwater management as well as for solving the inverse problem of parameter estimation. We will use numerical experiments and real case studies to show how this new, robust methodology can be used to drastically reduce the computational demand, while maintaining a significant degree of accuracy. The NSF portion of the work focuses on error analysis of the reduced model, which is a key component of the proposed research. Additionally, we will focus on verification of the proposed methodology using field data for parameter estimation and conjunctive use of surface water and groundwater. We have made arrangements with the Calleguas Municipal Water District (CMWD) in southern California for collaboration.

这是一项提交给NSF和ARO的联合支持提案，每个机构都被要求为提案的独立但相关的方面提供资金。我们建议开发可用于模型简化的技术，从而将复杂的完整模型替换为较小的简单近似值，该近似值在所需的精度范围内产生输出。我们提出的方法结合了数据驱动和模型驱动的方法，它利用了输入/输出数据关系，以及结合了物理模型。该建议的首要目标是制定和推广模型简化通过适当的正交分解在地下水建模在一个，两个和三个维度，并开发一个协议的基础上的结构的控制方程和模型的参数的快照选择。我们还将提出程序，减少模型用于地下水管理以及解决参数估计的逆问题。我们将使用数值实验和真实的案例研究来展示如何使用这种新的，强大的方法来大大减少计算需求，同时保持显着的准确度。NSF部分的工作重点是简化模型的误差分析，这是拟议研究的关键组成部分。此外，我们将重点验证所提出的方法，使用现场数据的参数估计和地表水和地下水的联合使用。我们已与加州南部的Calleguas市政水务区（CMWD）达成合作协议。