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首页> 外文期刊>Journal of Hydroinformatics >Quantitative methods to direct exploration based on hydrogeologic information
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Quantitative methods to direct exploration based on hydrogeologic information

机译：基于水文地质信息的定量勘探方法

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摘要

Quantitatively Directed Exploration (QDE) approaches based on information such as model sensitivity, input data covariance and model output covariance are presented. Seven approaches for directing exploration are developed, applied, and evaluated on a synthetic hydrogeologic site. The QDE approaches evaluate input information uncertainty, subsurface model sensitivity and, most importantly, output covariance to identify the next location to sample. Spatial input parameter values and covariances are calculated with the multivariate conditional probability calculation from a limited number of samples. A variogram structure is used during data extrapolation to describe the spatial continuity, or correlation, of subsurface information. Model sensitivity can be determined by perturbing input data and evaluating output response or, as in this work, sensitivities can be programmed directly into an analysis model. Output covariance is calculated by the First-Order Second Moment (FOSM) method, which combines the covariance of input information with model sensitivity. A groundwater flow example, modeled in MODFLOW-2000, is chosen to demonstrate the seven QDE approaches. MODFLOW-2000 is used to obtain the piezometric head and the model sensitivity simultaneously. The seven QDE approaches are evaluated based on the accuracy of the modeled piezometric head after information from a QDE sample is added. For the synthetic site used in this study, the QDE approach that identifies the location of hydraulic conductivity that contributes the most to the overall piezometric head variance proved to be the best method to quantitatively direct exploration.
机译：提出了基于模型敏感性，输入数据协方差和模型输出协方差等信息的定量定向探索（QDE）方法。在综合水文地质现场开发，应用和评估了七种指导勘探的方法。 QDE方法评估输入信息的不确定性，地下模型的敏感性以及最重要的是输出协方差，以识别下一个要采样的位置。空间输入参数值和协方差是通过有限数量的样本的多条件条件概率计算来计算的。在数据外推过程中使用变异函数结构来描述地下信息的空间连续性或相关性。可以通过扰动输入数据并评估输出响应来确定模型灵敏度，或者，如在本工作中一样，可以将灵敏度直接编程到分析模型中。输出协方差是通过一阶第二矩（FOSM）方法计算的，该方法将输入信息的协方差与模型灵敏度相结合。选择了以MODFLOW-2000为模型的地下水流实例来演示这七个QDE方法。 MODFLOW-2000用于同时获得测压头和模型灵敏度。在添加来自QDE样本的信息之后，基于建模的测压头的准确性评估这七个QDE方法。对于本研究中使用的合成场地，识别出对总测压头变化最大的水力传导率位置的QDE方法被证明是定量指导勘探的最佳方法。

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