Physics-informed spatiotemporal graph neural network models for groundwater contaminant prediction
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Groundwater contamination prediction is challenging because of the strong concealment, complex spatiotemporal coupling, and high parameter dependence of physical mechanism models. However, traditional data-driven models lack spatial representations. To address... ...
