Parameterization, sensitivity analysis, and inversion: an investigation using groundwater modeling of the surface-mined Tivoli-Guidonia basin (Metropolitan City of Rome, Italy) | Paramétrage, analyse de sensibilité et inversion: une étude utilisant la modélisation des eaux souterraines du bassin de Tivoli-Guidonia (Métropole de Rome, Italie) avec une exploitation du sous-sol Parametrización, análisis de sensibilidad e inversión: una investigación utilizando modelos de agua subterránea de la cuenca con minería de superficie del Tivoli-Guidonia (Ciudad Metropolitana de Roma, Italia) 参数化、灵敏度分析和反演:采用地下水模拟对(意大利罗马市)露天开采的Tivoli-Guidonia盆地进行调查 Parametrização, análise de sensibilidade e inversão: uma investigação utilizando modelagem de águas subterrâneas da bacia superficialmente mineirada Tivoli-Guidonia (Cidade Metropolitana de Roma, Itália)
2016
La Vigna, Francesco | Hill, Mary C. | Rossetto, Rudy | Mazza, Roberto
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, groundwater 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 Tivoli-Guidonia 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.
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