Contaminant Source Identification in Aquifers: A Critical View

Forty years and 157 papers later, research on contaminant source identification has grown exponentially in number but seems to be stalled concerning advancement towards the problem solution and its field application. This paper presents a historical evolution of the subject, highlighting its major advances. It also shows how the subject has grown in sophistication regarding the solution of the core problem (the source identification), forgetting that, from a practical point of view, such identification is worthless unless it is accompanied by a joint identification of the other uncertain parameters that characterize flow and transport in aquifers.

Using the Backward Probability Method in contaminant source identification with a finite-duration source loading in a river

Violation of industries in discharging their effluents into rivers leads to river pollution, which endangers the environment and human health. Appropriate tools are needed to deal with violations and protect rivers. The Backward Probability Method (BPM) is one of the most recommended tools identifying the release time and location of the pollutant source. However, the BPM generally was developed for groundwater and spill injection. Since most industries inject their effluents with a constant rate for a finite-duration, the use of prevailing models will have some errors. In this study, a numerical model was developed that could simulate a source with either a finite-duration or spill injection. This model is verified for two hypothetical cases and one real case. The results show that the model can accurately identify the release time and location of the pollutant source.

Identifying Contaminant Intrusion in Water Distribution Networks under Water Flow and Sensor Report Time Uncertainties

Contamination events in water distribution networks (WDNs) could have severe health and economic consequences. Contaminants can be deliberately or accidentally introduced into the WDN. Quick identification of the injection location and time is important in devising a mitigation plan to prevent further spread of the contaminant in the network. A method of identifying the possible intrusion point in a given network and reporting data is to use an inverse calculation by backtracking the potential path of the contaminant in the network. However, there is an element of uncertainty in the data used for calculation, particularly in water flow and sensor report time. Given the uncertainties, a method was developed in this study for fast and accurate contaminant source identification. This paper proposes a comparison filter of results by first identifying potential contaminant locations through backtracking, followed by a forward calculation to determine the injection time range, thereby reducing the potential suspects and providing likeliness comparison among the suspects. The effectiveness of the proposed method was examined by applying it to a benchmark WDN. By simulating uncertainties and filtering through the results, several possible contaminant intrusion locations and times were identified.