期刊
WATER RESEARCH
卷 213, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.watres.2022.118145
关键词
STANMOD CXTFIT; 2RNE non-equilibrium transport model; Water resources; Sensitivity analyses; Environmental forensics
资金
- Federal Ministry of Education and Research (BMBF) [02WRS1277A-C]
- Deutsche Forschungsgemeinschaft (DFG) [421036093]
This study introduces a transport-based source tracking method for identifying contamination sources in karst aquifers, which complements microbial and chemical source tracking techniques. The model is robust, requires reliable estimates of transport velocity and input time, and can be applied in cases where traditional numerical models lack sufficient data. Sensitivity analyses show that the model is highly sensitive to input time, flow velocity, and the fraction of mobile fluid region.
Identification and location of contamination sources is crucial for water resource protection - especially in karst aquifers which provide 25% of the world's population with water but are highly vulnerable to contamination. Transport-based source tracking is proposed and verified here as a complementary approach to microbial and chemical source tracking in karst aquifers for identifying and locating such sources of contamination and for avoiding ambiguities that might arise from using one method alone. The transport distance is inversely modelled from contaminant breakthrough curves (BTC), based on analytical solutions of the 1D two-region non-equilibrium advection dispersion equation using GNU Octave. Besides the BTC, the model requires reliable estimates of transport velocity and input time. The model is shown to be robust, allows scripted based, automated 2D sensitivity analyses (interplay of two parameters), and can be favourable when distributed numerical models are inappropriate due to insufficient data. Sensitivity analyses illustrate that the model is highly sensitive to the input time, the flow velocity, and the fraction of the mobile fluid region. A conclusive verification approach was performed by applying the method to synthetic data, tracer tests, and event-based field data. Transport distances were correctly modelled for a set of artificial tracer tests using a discharge-velocity relationship that could be established for the respective karst catchment. For the first time such an approach was shown to be applicable to estimate the maximum distance to the contamination source for coliform bacteria in karst spring water combined with microbial source tracking. However, prediction intervals for the transport distance can be large even in well-studied karst catchments mainly related to uncertainties in the flow velocity and the input time. Using a maximum transport distance is proposed to account for less permeable, slower pathways. In general, transport-based source tracking might be used wherever transport can be described by the 1D two-region non-equilibrium model, e.g. rivers and fractured or porous aquifers.
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