Dipartimento di Ingegneria Civile e Ambientale (DICA), Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy.
Dipartimento di Ingegneria Civile e Ambientale (DICA), Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy.
Sci Total Environ. 2021 Jan 10;751:141430. doi: 10.1016/j.scitotenv.2020.141430. Epub 2020 Aug 3.
The study introduces a comprehensive framework for natural springs' protection and probabilistic risk assessment in the presence of uncertainty associated with the characterization of the groundwater system. The methodology is applied to a regional-scale hydrogeological setting, located in Northern Italy and characterized by the presence of high-quality natural springs forming a unique system whose preservation is of critical importance for the region. Diverse risk pathways are presented to constitute a fault tree model enabling identification of all basic events, each associated with uncertainty and contributing to an undesired system failure. The latter is quantified in terms of hydraulic head falling below a given threshold value for at least one amongst all active springs. The workflow explicitly includes the impact of model parameter uncertainty on the evaluation of the overall probability of system failure due to alternative groundwater extraction strategies. To cope with conceptual model uncertainty, two models based on different reconstructions of the aquifer geological structure are considered. In each conceptual model, hydraulic conductivities related to the geomaterials composing the aquifer are affected by uncertainty. It is found that (a) the type of conceptual model employed to characterize the aquifer structure strongly affects the probability of system failure and (b) uncertainties associated with the ensuing conductivity fields, even as constrained through model calibration, lead to different impacts on the variability of hydraulic head levels at the springs depending on the conceptual model adopted. The results of the study demonstrate that the proposed approach enables one to (i) quantify the risk associated with springs depletion due to alternative strategies of aquifer exploitation; (ii) quantify the way diverse sources of uncertainty (i.e., model and parameter uncertainty) affect the probability of system failure; (iii) determine the optimal exploitation strategy ensuring system functioning; and (iv) identify the most vulnerable springs, where depletion first occurs.
本研究提出了一个综合框架，用于保护天然泉以及在与地下水系统特征化相关的不确定性存在的情况下进行概率风险评估。该方法应用于一个位于意大利北部的区域水文地质背景，其特点是存在高质量的天然泉，形成了一个独特的系统，其保护对该地区至关重要。提出了多种风险途径来构成故障树模型，从而识别所有基本事件，每个事件都与不确定性相关联，并导致系统发生不期望的故障。后者被量化为至少一个活跃泉的水头下降到给定阈值以下的情况。该工作流程明确包括由于替代地下水开采策略，模型参数不确定性对系统故障总概率评估的影响。为了应对概念模型不确定性，考虑了两种基于含水层地质结构不同重建的模型。在每个概念模型中，与构成含水层的地质材料相关的水力传导率受到不确定性的影响。研究结果表明：(a) 用于描述含水层结构的概念模型类型强烈影响系统故障的概率；(b) 即使通过模型校准来约束，与随之而来的传导场相关的不确定性，根据采用的概念模型，对泉水位变化的影响也不同。该研究的结果表明，所提出的方法能够：(i) 量化由于替代含水层开采策略导致的泉水枯竭相关风险；(ii) 量化多种不确定性源（即模型和参数不确定性）对系统故障概率的影响；(iii) 确定确保系统运行的最佳开采策略；以及 (iv) 识别最脆弱的泉，即首先发生枯竭的泉。
