Combined Methods from Entity and Field Frameworks to Determine the Source Characteristics of a Contaminant
While these methods are valuable, it becomes risky to implement them when spatial observations of a contaminant are sparse or when more than one entity is present in the sensor domain. For these situations, we must make use of all meteorological data available, and also may need to assume a plume/puff shape. This assumption implies a mixed Entity/Field approach because the field is matched to determine an entity state. To overcome limitations of a sparse data set, we can fit the data to a dispersion model at each time step to use contaminant observations for a greater period than one time instant. This will enable accurate determination of plume/puff spread, a quantity that is crucial to determine the contaminant source. Fitting the data will also allow us to ascertain the number of entities present in the sensor domain; however, an iterative procedure is used here to fit the contaminant data to ensure that the field is approximated by the correct number of entities. With these advances to the models, it will be shown that this combined Entity/Field approach will allow accurate determination of source characteristics of multiple plumes/puffs.