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An integrated data fusion approach to use geophysical measurements in hydrological models

An integrated data fusion approach to use geophysical measurements in hydrological models
在水文模型中使用地球物理测量的综合数据融合方法
批准号:
51319586
负责人:
Professor Dr. Johan Huisman
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
2007
资助国家:
德国
项目状态:
已结题
起止时间:
2006-12-31 至 2011-12-31

项目摘要

项目成果

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中文摘要
翻译
地球物理测量是水文模型参数化的宝贵信息来源。传统上,关于水文特性和/或状态变量的相关信息是通过地球物理测量以顺序方式获得的:首先对地球物理测量数据进行反演,然后在水文模型中使用由此获得的信息。该项目的目的是进一步开发一种替代的所谓耦合水文地球物理反演方法,以便在水文模型中使用地球物理数据,以克服序贯方法的一些局限性。在这一方法中,通过将地球物理测量的正演模型与水文模型相耦合,并通过摄动相关的水文流量和传输参数来最小化模拟数据与观测数据之间的差异,将地球物理测量直接包括在水文反问题中。这种耦合反演方法的开发是在该项目的第一阶段开始的。在第二阶段,它将在两个实验数据集上进一步开发和测试,这两个实验数据集包括饱和区的电阻率测量和非饱和区的自然电位和电阻率测量。第一数据集已经被获取,并且第二数据集将在该第二阶段被获取。对这些实验的分析将旨在从现有的地球物理和常规水文测量中确定有效的和空间可变的流动和输送特性。
英文摘要
Geophysical measurements are a valuable source of information for the parameterization of hydrological models. Traditionally, relevant information on hydrological properties and/or state variables is obtained in a sequential approach from geophysical measurements: the geophysical survey data are inverted first, and the information thus obtained is used within the hydrological model. The aim of this project is to further develop an alternative so-called coupled hydrogeophysical inversion approach to use geophysical data in hydrological models that overcomes some of the limitations of the sequential approach. In this approach, geophysical measurements are directly included in the hydrological inverse problem by coupling a forward model of the geophysical measurements with a hydrological model and minimizing the difference between modeled and observed data by perturbing the relevant hydrological flow and transport parameters. The development of this coupled inversion approach was started in the first phase of the project. In this second phase, it will be further developed and tested on two experimental data sets consisting of electrical resistivity measurements in the saturated zone and self-potential and electrical resistivity measurements in the unsaturated zone. The first data set has already been acquired and the second data set will be acquired in this second phase. The analysis of these experiments will aim to determine both effective and spatially variable flow and transport properties from the available geophysical and conventional hydrological measurements.
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国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
复杂数据下半参数转换模型及其在老年慢性病发展中的应用研究
  • 批准号:
    72101261
  • 项目类别:
    青年科学基金项目(C类)
  • 资助金额:
    30.0万元
  • 批准年份:
    2021
  • 负责人:
    孙韬
  • 依托单位:
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位: