Delineating Drinking Water Protection Areas Using Analytic Element Models (AEMs) With Focus on Enabling Uncertainty Analysis Using Monte Carlo Simulations

Typ
Examensarbete för masterexamen
Master's Thesis
Program
Infrastructure and environmental engineering (MPIEE), MSc
Publicerad
2023
Författare
ZAMZAMI, MARYAM
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The delineation of a wellhead protection area (WHPA) is a crucial task aimed at safeguarding underground water resources. There are various methods available to achieve this, ranging from simple approaches like fixed radius estimation with inherent limitations to more sophisticated numerical models, which are considered the most detailed and reliable but timeconsuming and data-intensive option. An analytical element model (AEM) provides a middle ground between these two extremes, offering users the flexibility to implement different boundary scenarios without being constrained by grid limitations. Moreover, AEM can perform better in cases where data is scarce. However, it is important to recognize that the output of groundwater modeling can never be claimed to fully reflect reality due to inherent uncertainties. These uncertainties arise from various sources, including conceptual understanding, model simplifications, and lack of data. To address these uncertainties, TimML, a multi-layer, analytic element model, is employed and further enhanced to enable Monte Carlo Simulations (MCS). To evaluate the effectiveness of the approach, a case study was selected in which eight different scenarios were considered and caclualtions performed using MCS to consider uncertainties. The calculated ranges of protection zones from these scenarios are illustrated for the study area and benchmarked against the outcomes of the wellhead analytical element model (WhAEM), an existing software for delineation of WHPAs tht does not enable MCS. The results from the TimML model illustrates the added value of considering parameter ucnertainties and how it affects the WHPA. Furthermore, the comparison reveals that the largest differences are between the different scenarios rather than the two applied models. This emphasizes the significant role of uncertainties arising from different assumptions in the case study, highlighting that stochastic modeling alone is not sufficient to capture all relevant uncertainties.
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Ämne/nyckelord
groundwater modeling, analytic element model, uncertainties, water protection, Monte Carlo analysis, stochastic modeling
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