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Parameterization, sensitivity analysis, and inversion: an investigation using groundwater modeling of the surface-mined Tivoli-Guidonia basin (Metropolitan City of Rome, Italy)

机译:参数化,敏感性分析和反演:使用地表开采的Tivoli-Guidonia盆地(意大利大都会罗马)的地下水模型进行的调查

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With respect to model parameterization and sensitivity analysis, this work uses a practical example to suggest that methods that start with simple models and use computationally frugal model analysis methods remain valuable in any toolbox of model development methods. In this work, ground-water model calibration starts with a simple parameterization that evolves into a moderately complex model. The model is developed for a water management study of the TivoliGuidonia basin (Rome, Italy) where surface mining has been conducted in conjunction with substantial dewatering. The approach to model development used in this work employs repeated analysis using sensitivity and inverse methods, including use of a new observation-stacked parameter importance graph. The methods are highly parallelizable and require few model runs, which make the repeated analyses and attendant insights possible. The success of a model development design can be measured by insights attained and demonstrated model accuracy relevant to predictions. Example insights were obtained: (1) A long-held belief that, except for a few distinct fractures, the travertine is homogeneous was found to be inadequate, and (2) The dewatering pumping rate is more critical to model accuracy than expected. The latter insight motivated additional data collection and improved pumpage estimates. Validation tests using three other recharge and pumpage conditions suggest good accuracy for the predictions considered. The model was used to evaluate management scenarios and showed that similar dewatering results could be achieved using 20 % less pumped water, but would require installing newly positioned wells and cooperation between mine owners.
机译:关于模型参数化和敏感性分析,该工作使用一个实际示例来说明,从简单模型开始并使用计算上节俭的模型分析方法的方法在任何模型开发方法工具箱中仍然有价值。在这项工作中,地下水模型校准从简单的参数化开始,然后演变为中等复杂的模型。该模型是针对TivoliGuidonia盆地(意大利罗马)的水管理研究而开发的,该地区已进行了地面采矿和大量脱水。在这项工作中使用的模型开发方法采用敏感性和反方法进行重复分析,包括使用新的观察堆叠参数重要性图。这些方法高度可并行化,几乎不需要模型运行,这使得重复的分析和附带的见解成为可能。模型开发设计的成功可以通过获得的见解和与预测相关的模型准确性来衡量。获得了以下示例的见解:(1)长期以来一直认为,除了少数几个明显的裂缝外,石灰华是均质的,而且(2)脱水抽速对模型精度的影响比预期的更为关键。后者的见解激发了更多的数据收集和改进的抽油量估算。使用其他三个补给和泵送条件的验证测试表明,所考虑的预测具有良好的准确性。该模型用于评估管理方案,结果表明,抽水量减少20%即可达到类似的脱水效果,但需要安装新定位的井并与矿主之间进行合作。

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