Inverse uncertainty characteristics of pollution source identification for river chemical spill incidents by stochastic analysis

Abstract

Uncertainty rules of pollution source inversion are revealed by stochastic analysis

A release load is most easily inversed and source locations own largest uncertainty

Instantaneous spill assumption has much less uncertainty than continuous spill

The estimated release locations and times negatively deviate from real values

The new findings improve monitoring network design and emergency response to spills

Identifying source information after river chemical spill occurrences is critical for emergency responses. However, the inverse uncertainty characteristics of this kind of pollution source inversion problem have not yet been clearly elucidated. To fill this gap, stochastic analysis approaches, including a regional sensitivity analysis method (RSA), identifiability plot and perturbation methods, were employed to conduct an empirical investigation on generic inverse uncertainty characteristics under a well-accepted uncertainty analysis framework. Case studies based on field tracer experiments and synthetic numerical tracer experiments revealed several new rules. For example, the release load can be most easily inverted, and the source location is responsible for the largest uncertainty among the source parameters. The diffusion and convection processes are more sensitive than the dilution and pollutant attenuation processes to the optimization of objective functions in terms of structural uncertainty. The differences among the different objective functions are smaller for instantaneous release than for continuous release cases. Small monitoring errors affect the inversion results only slightly, which can be ignored in practice. Interestingly, the estimated values of the release location and time negatively deviate from the real values, and the extent is positively correlated with the relative size of the mixing zone to the objective river reach. These new findings improve decision making in emergency responses to sudden water pollution and guide the monitoring network design.

Graphical abstract

Keywords

River chemical spills / Emergency response / Pollution source inversion / Inverse uncertainty analysis / Regional Sensitivity Analysis method (RSA) / Monte Carlo analysis toolbox (MCAT)

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