Abstract
The study proposes a stochastic approach to quantify the uncertainty of groundwater vulnerability (GV) produced by classical index-overlay methods. In the analysis, the physical-based MODFLOW model has been integrated with the DRASTIC method and modified by the analytical hierarchy process (AHP) technique. Specifically, the flow fields from the MODFLOW model provide the parameters of depth to water and the associated hydraulic conductivity (K) for the DRASTIC method. The integrated loops between the MODFLOW and DRASTIC models enable the evaluations of GV maps by considering sources of uncertainty in geological parameters and stress changes in an aquifer system. In illustrating the approach for practical implementations, the study considers the uncertainty produced by the heterogeneity of K in the Pingtung Plain groundwater basin in southern Taiwan. Different degrees of K heterogeneity were assessed to quantify the impact of the K heterogeneity on the GV mappings. Results show that the integration of parameter uncertainty information from the stochastic-based approach for GV mapping can improve the accuracy and reliability of the GV assessment. The stochastic GV maps have accounted for the source of the K uncertainty. There are significant discrepancies in GV values in the spatial distribution and intensity in all GV classes. The results clarify the potential risk of groundwater contamination in the Pingtung Plain groundwater basin.
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Acknowledgements
The author would like to thank the Taiwan Central Geological Survey and Water Resources Agency for collecting data.
Funding
The Ministry of Science and Technology partially supported this research, the Republic of China under grants MOST 109-2621-M-008-003, MOST 110-2621-M-008-003, MOST 111-2621-M-008-003, and MOST 111-2122-M-002-001.
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CFN and TDV conceived the main idea of the paper. CFN and TDV developed and tested the models. TDV, WCL, MTT, and VCB prepared the figures and tables. CFN, TDV, WCL, and MHT wrote the paper. All authors read and approved the final draft.
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Ni, CF., Vu, TD., Li, WC. et al. Stochastic-based approach to quantify the uncertainty of groundwater vulnerability. Stoch Environ Res Risk Assess 37, 1897–1915 (2023). https://doi.org/10.1007/s00477-022-02372-2
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DOI: https://doi.org/10.1007/s00477-022-02372-2