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Integrating collocated auxiliary parameters in geostatistical simulations using joint probability distributions and probability aggregation

机译：使用联合概率分布和概率聚合在地统计学模拟中整合并置的辅助参数

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摘要

We propose a new cosimulation algorithm for simulating a primary attribute using one or several secondary attributes known exhaustively on the domain. This problem is frequently encountered in surface and groundwater hydrology when a variable of interest is measured only at a discrete number of locations and when the secondary variable is mapped by indirect techniques such as geophysics or remote sensing. In the proposed approach, the correlation between the two variables is modeled by a joint probability distribution function. A technique to construct such relation using underlying variables and physical laws is proposed when field data are insufficient. The simulation algorithm proceeds sequentially. At each location of the domain, two conditional probability distribution functions (cpdf) are inferred. The cpdf of the main attribute is inferred in a classical way from the neighboring data and a model of spatial variability. The second cpdf is inferred directly from the joint probability distribution function of the two attributes and the value of the secondary attribute at the location to be simulated. The two distribution functions are combined by probability aggregation to obtain the local cpdf from which a value for the primary attribute is randomly drawn. Various examples using synthetic and remote sensing data demonstrate that the method is more accurate than the classical collocated cosimulation technique when a complex relation relates the two attributes.
机译：我们提出了一种新的协同仿真算法，该算法使用域上详尽了解的一个或几个辅助属性来模拟主要属性。当仅在离散位置测量感兴趣的变量，并且通过间接技术（例如地球物理或遥感）映射次要变量时，在地表和地下水水文学中经常会遇到此问题。在提出的方法中，两个变量之间的相关性通过联合概率分布函数建模。当现场数据不足时，提出了一种使用基础变量和物理定律构造这种关系的技术。仿真算法按顺序进行。在域的每个位置，推断出两个条件概率分布函数（cpdf）。主要属性的cpdf是用经典方法从相邻数据和空间变异性模型中推断出来的。第二个cpdf直接从两个属性的联合概率分布函数以及要模拟的位置处的次要属性的值推论得出。通过概率聚集将两个分布函数组合在一起，以获取局部cpdf，从中随机抽取主要属性的值。使用合成和遥感数据的各种示例表明，当复杂关系涉及两个属性时，该方法比经典的并置协同仿真技术更准确。

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  • 来源
    《Water resources research》 |2009年第8期|W08421.1-W08421.13|共13页
  • 作者

    Gregoire Mariethoz; Philippe Renard; Roland Froidevaux;

  • 作者单位

    Centre for Hydrogeology, University of Neuchatel, 11 Rue Emile Argand, CP 158, CH-2000 Neuchatel, Switzerland;

    Centre for Hydrogeology, University of Neuchatel, 11 Rue Emile Argand, CP 158, CH-2000 Neuchatel, Switzerland;

    Ephesia Consult, 9, rue Boissonnas, CH-1227 Geneva, Switzerland;

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