GroMoPo Metadata for Tivoli-Guidonia basin model

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.在模型参数化与敏感性分析领域，本研究通过实际案例表明，从简单模型起步、采用低计算开销的模型分析方法的建模思路，在各类模型开发方法工具箱中仍具备重要价值。本研究中的地下水模型校准，从简单参数化方案出发，逐步演进为中等复杂度的模型。该模型是为意大利罗马蒂沃利-圭多尼亚盆地（TivoliGuidonia Basin）的水资源管理研究开发的，该区域曾开展露天采矿作业并伴随大规模疏干排水作业。本研究采用的模型开发方法，通过重复开展敏感性分析与反演分析，其中还引入了一种新型的观测堆叠式参数重要性图（observation-stacked parameter importance graph）。该方法具备高度可并行性，且仅需少量模型运行次数，从而支撑了重复分析与相关研究见解的获取。模型开发方案的有效性，可以通过所获得的研究见解以及与预测相关的模型验证精度来衡量。本研究获得了两项典型结论：(1) 长期以来认为除少数明显裂隙外钙华（travertine）均质性良好的观点，被证实并不准确；(2) 疏干排水抽水量对模型精度的影响比预期更为关键。第二项结论推动了后续的数据采集工作，并优化了抽水量估算方案。利用另外三种补给与抽采条件开展的验证试验结果表明，所研究的预测方案具备良好精度。该模型被用于评估多种水资源管理方案，结果显示，仅需减少20%的抽水量即可达到相近的排水效果，但需要布设新位置的抽水井，并协调各矿主之间的合作。